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Heterogeneous uptake of SO2 on mineral dust is a predominant formation pathway of sulfates, whereas the contribution of photo-induced SO2 oxidation to sulfates on the dust interfaces still remains unclear. Here, we investigated heterogeneous photochemical reactions of SO2 on five mineral oxides (SiO2, kaolinite, Al2O3, MgO, and CaO) without photocatalytic activity. Light enhanced the uptake of SO2, and its enhancement effects negatively depended on the basicity of mineral oxides. The initial uptake coefficient (γ0,BET) and the steady-state uptake coefficient (γs,BET) of SO2 positively relied on light intensity, relative humidity (RH), and O2 content, while they exhibited a negative relationship with the initial SO2 concentration. Rapid sulfate formation during photo-induced heterogeneous reactions of SO2 with all mineral oxides was confirmed to be ubiquitous, and H2O and O2 played key roles in the conversion of SO2 to sulfates. In particular, triplet states of SO2 (3SO2) were suggested to be the trigger for photochemical sulfate formation. Atmospheric implications supported a potential contribution of interfacial SO2 photochemistry on non-photoactive mineral dust to atmospheric sulfate sources.

A larger antecedent effective precipitation (AEP) indicates a higher probability of a debris flow (Pdf) being triggered by subsequent rainfall. Scientific topics surrounding this qualitative conclusion that can be raised include what kinds of variation rules they follow and whether there is a boundary limit. To answer these questions, Jiangjia Gully in Dongchuan, Yunnan Province, China, is chosen as the study area, and numerical calculation, a rainfall scenario simulation, and the Monte Carlo integration method have been used to calculate the occurrence probability of debris flow under different AEP conditions and derive the functional relationship between Pdf and AEP. The relationship between Pdf and AEP can be quantified by a piecewise function. Pdf is equal to 15.88 %, even when AEP reaches 85 mm, indicating that debris flow by nature has an extremely small probability compared to the rainfall frequency. Data from 1094 rainfall events and 37 historical debris flow events are collected to verify the reasonability of the functional relationship. The results indicate that the piecewise functions are highly correlated with the observation results. Our study confirms the correctness of the qualitative description of the relationship between AEP and Pdf, clarifies that debris flow is a small-probability event compared to rainfall frequency, and quantitatively reveals the evolution law of debris flow occurrence probability with AEP. All the above discoveries can provide a clear reference for the early warning of debris flows.

Carbonyl sulfide (COS), a trace gas in our atmosphere that leads to the formation of aerosols in the stratosphere, is largely taken up by terrestrial ecosystems. Quantifying the biosphere uptake of COS could provide a useful quantity to estimate gross primary productivity (GPP). Some COS sources and sinks still contain large uncertainties, and several top-down estimates of the COS budget point to an underestimation of sources, especially in the tropics. We extended the inverse model TM5-4DVAR to assimilate Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) satellite data, in addition to National Oceanic and Atmospheric Administration (NOAA) surface data as used in a previous study. To resolve possible discrepancies among the two observational data sets, a bias correction scheme is necessary and implemented. A set of inversions is presented that explores the influence of the different measurement streams and the settings of the prior fluxes. To evaluate the performance of the inverse system, the HIAPER Pole-to-Pole Observations (HIPPO) aircraft observations and NOAA airborne profiles are used. All inversions reduce the COS biosphere uptake from a prior value of 1053 GgS a−1 to much smaller values, depending on the inversion settings. These large adjustments of the biosphere uptake often turn parts of Amazonia into a COS source. Only inversions that exclusively use MIPAS observations, or strongly reduce the prior errors on the biosphere flux, maintain the Amazon as a COS sink. Inclusion of MIPAS data in the inversion leads to a better separation of land and ocean fluxes. Over the Amazon, these inversions reduce the biosphere uptake from roughly 300 to 100 GgS a−1, indicating a strongly overestimated prior uptake in this region. Although a recent study also reported reduced COS uptake over the Amazon, we emphasise that a careful construction of prior fluxes and their associated errors remains important. For instance, an inversion that gives large freedom to adjust the anthropogenic and ocean fluxes of CS2, an important COS precursor, also closes the budget satisfactorily with much smaller adjustments to the biosphere. We achieved better characterisation of biosphere prior and uncertainty, better characterisation of combined ocean and land fluxes, and better constraint of both by combining surface and satellite observations. We recommend more COS observations to characterise biosphere and ocean fluxes, especially over the data-poor tropics.

In order to determine the most suitable turbulence model for studying the aerodynamic performance of bus, the effects of different turbulence models on the aerodynamic characteristics of bus were investigated. A comparative analysis was conducted on five turbulence models (IDDES, DDES, DES, LES, URANS). The pressure distribution on the cross section at x=0 and y=0 is also analyzed for each model. The results reveal that IDDES accurately captures the negative pressure at the rear of the bus and predicts the pressure gradients more effectively than other models. IDDES also captures more vortices at the head of the bus and predicts the wake flow more widely than other models. DDES has obvious shedding phenomenon in the wake flow, while IDDES provides a relatively smooth airflow trajectory, but its prediction of airflow trajectory at a distance is less clear. Through quantitative and qualitative analyses of the aerodynamic characteristics of bus under different turbulence models, it can be concluded that IDDES is the most suitable turbulence model to study the aerodynamic characteristics of bus.

The El Niño–Southern Oscillation (ENSO) is a significant climate phenomenon that appears periodically in the tropical Pacific. The intermediate coupled ocean–atmosphere Zebiak–Cane (ZC) model is the first and classical one designed to numerically forecast the ENSO events. Traditionally, the conditional nonlinear optimal perturbation (CNOP) approach has been used to capture optimal precursors in practice. In this paper, based on state-of-the-art statistical machine learning techniques1, we investigate the sampling algorithm proposed in Shi and Sun (2023) to obtain optimal precursors via the CNOP approach in the ZC model. For the ZC model, or more generally, the numerical models with a large number O(104−105) of degrees of freedom, the numerical performance, regardless of the statically spatial patterns and the dynamical nonlinear time evolution behaviors as well as the corresponding quantities and indices, shows the high efficiency of the sampling method compared to the traditional adjoint method. The sampling algorithm does not only reduce the gradient (first-order information) to the objective function value (zeroth-order information) but also avoids the use of the adjoint model, which is hard to develop in the coupled ocean–atmosphere models and the parameterization models. In addition, based on the key characteristic that the samples are independently and identically distributed, we can implement the sampling algorithm by parallel computation to shorten the computation time. Meanwhile, we also show in the numerical experiments that the important features of optimal precursors can still be captured even when the number of samples is reduced sharply.

In this paper, a novel series three-axis stable platform (STSP) is proposed, and its azimuth angle structure, pitch angle structure, roll angle structure, overall system structure scheme, and control scheme are designed. The platform is a universal one. The forward and inverse kinematics and dynamics models of the STSP pitch-and-roll mechanisms are established, and the motion rules of the platform and the force conditions of the main components are analyzed. Establish a mathematical model of the platform control system, analyze the performance of the pitch-and-roll system of the STSP, propose a position velocity dual-closed-loop control strategy, and determine the controller parameters through simulation analysis of the control system. A comprehensive experiment is carried out to install the STSP on the swing platform; simulate the actual operating environment, verify the rationality and dynamic accuracy of the kinematic model, dynamic model, and control strategy; and verify the feasibility and stability of the system control scheme and platform configuration.

Land surface temperature (LST) is a key variable within Earth's climate system and a necessary input parameter required by numerous land–atmosphere models. It can be directly retrieved from satellite thermal infrared (TIR) observations, which contain many invalid pixels mainly caused by cloud contamination. To investigate the spatial and temporal variations in LST in China, long-term, high-quality, and spatiotemporally continuous LST datasets (i.e., all-weather LST) are urgently needed. Fusing satellite TIR LST and reanalysis datasets is a viable route to obtain long time-series all-weather LSTs. Among satellite TIR LSTs, the MODIS LST is the most commonly used, and a few corresponding all-weather LST products have been reported recently. However, the publicly reported all-weather LSTs were not available during the temporal gaps of MODIS between 2000 and 2002. In this study, we generated a daily (four observations per day) 1 km all-weather LST dataset for China's landmass and surrounding areas, the Thermal and Reanalysis Integrating Moderate-resolution Spatial-seamless (TRIMS) LST, which begins on the first day of the new millennium (1 January 2000). We used the enhanced reanalysis and thermal infrared remote sensing merging (E-RTM) method to generate the TRIMS LST dataset with the temporal gaps being filled, which had not been achieved by the original RTM method. Specifically, we developed two novel approaches, i.e., the random-forest-based spatiotemporal merging (RFSTM) approach and the time-sequential LST-based reconstruction (TSETR) approach, respectively, to produce Terra/MODIS-based and Aqua/MODIS-based TRIMS LSTs during the temporal gaps. We also conducted a thorough evaluation of the TRIMS LST. A comparison with the Global Land Data Assimilation System (GLDAS) and ERA5-Land LST demonstrates that the TRIMS LST has similar spatial patterns but a higher image quality, more spatial details, and no evident spatial discontinuities. The results outside the temporal gap show consistent comparisons of the TRIMS LST with the MODIS LST and the Advanced Along-Track Scanning Radiometer (AATSR) LST, with a mean bias deviation (MBD) of 0.09/0.37 K and a standard deviation of bias (SD) of 1.45/1.55 K. Validation based on the in situ LST at 19 ground sites indicates that the TRIMS LST has a mean bias error (MBE) ranging from −2.26 to 1.73 K and a root mean square error (RMSE) ranging from 0.80 to 3.68 K. There is no significant difference between the clear-sky and cloudy conditions. For the temporal gap, it is observed that RFSTM and TSETR perform similarly to the original RTM method. Additionally, the differences between Aqua and Terra remain stable throughout the temporal gap. The TRIMS LST has already been used by scientific communities in various applications such as soil moisture downscaling, evapotranspiration estimation, and urban heat island modeling. The TRIMS LST is freely and conveniently available at https://doi.org/10.11888/Meteoro.tpdc.271252 (Zhou et al., 2021).

The fraction of light absorbed in a material is a key parameter for a wide range of optoelectronic and energy devices, including solar cells, light emitting diodes, and photo(electro)chemical devices. It can reveal detailed performance information and establish a material’s theoretical efficiency limits. However, measuring absorption accurately is challenging, especially due to scattering effects at the macroscale and achieving perpendicular illumination over a small area at the microscale. In this tutorial, we present concepts and best practices in measuring absorption at both the macro- and micro-scale. We also give examples of using absorption to reveal critical optoelectronic information in energy devices. This work aims at standardizing the recording of absorption measurements across a number of fields, allowing for improved microscale understanding of a wide range of samples.

Associations between tropospheric ozone (O3) and climate variations have been extensively investigated worldwide. However, given the lack of historical O3 monitoring data, the knowledge gaps regarding the influences of climate variations on long-term O3 trends in China remain. The present study used a tropospheric O3 dataset from the summers of 1999 to 2017 simulated by an atmospheric chemistry model to explore the linkage between summer O3 and a dominant atmospheric circulation system – the Western Pacific Subtropical High (WPSH) pressure – on an interannual basis in China. During this period, both WPSH strength and O3 concentrations in eastern and central China illustrated a growing trend. An EOF analysis was conducted to examine significant summer O3 characteristics and patterns and their potential connections with the WPSH. We find that the correlation between the first principal component of summer ozone concentration in the EOF analysis and the WPSH reached 0.56 (P≤0.01) in China from 1999 to 2017. We show that the WPSH determines interannual fluctuations of summer O3, whereas O3 precursor emissions contribute primarily to the O3 long-term trend. Our results reveal that the WPSH plays a vital role in O3 perturbation in the eastern seaboard regions and inland China. Precursor emissions made more significant contributions of up to 60 % to increasing O3 trends in the inland urban agglomerations than coastal regions in eastern and southern China. The strongest contribution of meteorological conditions associated with the WPSH to summer O3 occurred in the Yangtze River Delta (YRD), accounting for over 9 % to ozone perturbations from 1999 to 2017. We find that the effect of the WPSH on regional O3 depends on the spatial proximity to the WPSH. We attributed the effects of the WPSH on O3 interannual variations to the changes in air temperature, precipitation, and winds associated with the WPSH's intensity and positions.

Tropospheric vertical column densities (VCDs) of nitrogen dioxide (NO2) retrieved from sun-synchronous satellite instruments have provided abundant NO2 data for environmental studies, but such data are limited by retrieval uncertainties and insufficient temporal sampling (e.g., once a day). The Geostationary Environment Monitoring Spectrometer (GEMS) launched in February 2020 monitors NO2 at an unprecedented hourly resolution during the daytime. Here we present a research product for tropospheric NO2 VCDs, referred to as POMINO–GEMS (where POMINO is the Peking University OMI NO2 algorithm). We develop a hybrid retrieval method combining GEMS, TROPOMI (TROPOspheric Monitoring Instrument) and GEOS-CF (Global Earth Observing System Composition Forecast) data to generate hourly tropospheric NO2 slant column densities (SCDs). We then derive tropospheric NO2 air mass factors (AMFs) with explicit corrections for surface reflectance anisotropy and aerosol optical effects through parallelized pixel-by-pixel radiative transfer calculations. Prerequisite cloud parameters are retrieved with the O2–O2 algorithm by using ancillary parameters consistent with those used in NO2 AMF calculations. The initial retrieval of POMINO–GEMS tropospheric NO2 VCDs for June–August 2021 exhibits strong hotspot signals over megacities and distinctive diurnal variations over polluted and clean areas. POMINO–GEMS NO2 VCDs agree with the POMINO–TROPOMI v1.2.2 product (R=0.98; NMB = 4.9 %) over East Asia, with slight differences associated with satellite viewing geometries and cloud and aerosol properties affecting the NO2 retrieval. POMINO–GEMS also shows good agreement with the following: OMNO2 (Ozone Monitoring Instrument (OMI) NO2 Standard Product) v4 (R=0.87; NMB = −16.8 %); and GOME-2 (Global Ozone Monitoring Experiment-2) GDP (GOME Data Processor) 4.8 (R=0.83; NMB = −1.5 %) NO2 products. POMINO–GEMS shows small biases against ground-based MAX-DOAS (multi-axis differential optical absorption spectroscopy) NO2 VCD data at nine sites (NMB = −11.1 %), with modest or high correlation in diurnal variation at six urban and suburban sites (R from 0.60 to 0.96). The spatiotemporal variation in POMINO–GEMS correlates well with mobile car MAX-DOAS measurements in the Three Rivers source region on the Tibetan Plateau (R=0.81). Surface NO2 concentrations estimated from POMINO–GEMS VCDs are consistent with measurements from the Ministry of Ecology and Environment of China for spatiotemporal variation (R=0.78; NMB = −26.3 %) and diurnal variation at all, urban, suburban and rural sites (R≥0.96). POMINO–GEMS data will be made freely available for users to study the spatiotemporal variations, sources and impacts of NO2.

Nowadays, timely monitoring of zoonotic agents, including salmonellosis, which are caused by various serovars of the family Salmonella, is relevant. Attention should be paid to the study of cytokine levels in combination with immunological studies. This helps clarify the pathogenesis of infectious diseases and develop preventive measures. The main purpose of study was to detect the process of regulating Th1/Th2 cytokines expression in chickens infected with salmonellosis. The field strain of S. Pullorum CVCC 530 was used in the research. The steE deletion mutant (ΔsteE) and steE-complemented ΔsteE:steE (ΔsteE+steE) strains were constructed in the WT strain using the λ-Red recombination method. Chickens were orally infected with WT, ΔsteE, and ΔsteE+steE strains (1×109 CFU/individual). The effect of steE on the host immune response remains unknown. Compared with the group infected with the WT or ΔsteE+steE strain, IL-12 and IFN-γ mRNA transcript levels were significantly higher, while IL-10 mRNA expression was significantly reduced in the liver and bursa infected with the ΔsteE strain; IL-4 showed a dramatically reduced transcription level, but IL-18 mRNA expression was significantly increased in the ΔsteE strain – spleen, cecum, and heart; IL-10 mRNA expression was significantly reduced in the spleen and cecum infected with the ΔsteE strain. These results suggest that steE may regulate the Th1/Th2 cytokine response balance in chickens infected with S. Pullorum and provide new insights into the pathogenesis of salmonellosis for the treatment of persistent infection

Carbonyl sulfide (COS) is a promising tracer for the estimation of terrestrial ecosystem gross primary production (GPP). However, understanding its non-GPP-related sources and sinks, e.g., anthropogenic sources and soil sources and sinks, is also critical to the success of the approach. Here we infer the regional sources and sinks of COS using continuous in situ mole fraction profile measurements of COS along the 60 m tall Lutjewad tower (1 m a.s.l.; 53∘24′ N, 6∘21′ E) in the Netherlands. To identify potential sources that caused the observed enhancements of COS mole fractions at Lutjewad, both discrete flask samples and in situ measurements in the province of Groningen were made from a mobile van using a quantum cascade laser spectrometer (QCLS). We also simulated the COS mole fractions at Lutjewad using the Stochastic Time-Inverted Lagrangian Transport (STILT) model combined with emission inventories and plant uptake fluxes. We determined the nighttime COS fluxes to be -3.0±2.6 pmol m−2 s−1 using the radon-tracer correlation approach and Lutjewad observations. Furthermore, we identified and quantified several COS sources, including biodigesters, sugar production facilities and silicon carbide production facilities in the province of Groningen. Moreover, the simulation results show that the observed COS enhancements can be partially explained by known industrial sources of COS and CS2, in particular from the Ruhr Valley (51.5∘ N, 7.2∘ E) and Antwerp (51.2∘ N, 4.4∘ E) areas. The contribution of likely missing anthropogenic sources of COS and CS2 in the inventory may be significant. The impact of the identified sources in the province of Groningen is estimated to be negligible in terms of the observed COS enhancements. However, in specific conditions, these sources may influence the measurements in Lutjewad. These results are valuable for improving our understanding of the sources and sinks of COS, contributing to the use of COS as a tracer for GPP.

High-frequency observations of the ice–ocean interaction and high-precision estimation of the ice–ocean heat exchange are critical to understanding the thermodynamics of the landfast ice mass balance in Antarctica. To investigate the oceanic contribution to the evolution of the landfast ice, an integrated ocean observation system, including an acoustic Doppler velocimeter (ADV), conductivity–temperature–depth (CTD) sensors, and a sea ice mass balance array (SIMBA), was deployed on the landfast ice near the Chinese Zhongshan Station in Prydz Bay, East Antarctica, from April to November 2021. The CTD sensors recorded the ocean temperature and salinity. The ocean temperature experienced a rapid increase in late April, from −1.62 to the maximum of −1.30 ∘C, and then it gradually decreased to −1.75 ∘C in May and remained at this temperature until November. The seawater salinity and density exhibited similar increasing trends during April and May, with mean rates of 0.04 psu d−1 and 0.03 kg m−3 d−1, respectively, which was related to the strong salt rejection caused by freezing of the landfast ice. The ocean current observed by the ADV had mean horizontal and vertical velocities of 9.5 ± 3.9 and 0.2 ± 0.8 cm s−1, respectively. The domain current direction was ESE (120∘)–WSW (240∘), and the domain velocity (79 %) was 5–15 cm s−1. The oceanic heat flux (Fw) estimated using the residual method reached a peak of 41.3 ± 9.8 W m−2 in April, and then it gradually decreased to a stable level of 7.8 ± 2.9 W m−2 from June to October. The Fw values calculated using three different bulk parameterizations exhibited similar trends with different magnitudes due to the uncertainties of the empirical friction velocity. The spectral analysis results suggest that all of the observed ocean variables exhibited a typical half-day period, indicating the strong diurnal influence of the local tidal oscillations. The large-scale sea ice distribution and ocean circulation contributed to the seasonal variations in the ocean variables, revealing the important relationship between the large-scale and local phenomena. The high-frequency and cross-seasonal observations of oceanic variables obtained in this study allow us to deeply investigate their diurnal and seasonal variations and to evaluate their influences on the landfast ice evolution.

We introduce the new Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 product of total column ozone (O3), total and tropospheric column nitrogen dioxide (NO2), total column water vapour, total column bromine oxide (BrO), total column formaldehyde (HCHO), and total column sulfur dioxide (SO2) (daily products https://doi.org/10.15770/EUM_SAF_AC_0048, AC SAF, 2023a; monthly products https://doi.org/10.15770/EUM_SAF_AC_0049, AC SAF, 2023b). The GOME-2 level-3 products aim to provide easily translatable and user-friendly data sets to the scientific community for scientific progress as well as to satisfy public interest. The purpose of this paper is to present the theoretical basis as well as the verification and validation of the GOME-2 daily and monthly level-3 products. The GOME-2 level-3 products are produced using the overlapping area-weighting method. Details of the gridding algorithm are presented. The spatial resolution of the GOME-2 level-3 products is selected based on the sensitivity study. The consistency of the resulting level-3 products among three GOME-2 sensors is investigated through time series of global averages, zonal averages, and bias. The accuracy of the products is validated by comparison to ground-based observations. The verification and validation results show that the GOME-2 level-3 products are consistent with the level-2 data. Small discrepancies are found among three GOME-2 sensors, which are mainly caused by the differences in the instrument characteristic and level-2 processor. The comparison of GOME-2 level-3 products to ground-based observations in general shows very good agreement, indicating that the products are consistent and fulfil the requirements to serve the scientific community and general public.

The greening impacts on China from 2000 to 2017 led to an increase in vegetated areas and thus enhanced biogenic volatile organic compound (BVOC) emissions. BVOCs are regarded as important precursors for ozone (O3) and secondary organic aerosol (SOA). As a result, accurate estimation of BVOC emissions is critical to understand their impacts on air quality. In this study, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) v2.1 was used to investigate the impact of different leaf area index (LAI) and land cover (LC) datasets on BVOC emissions in China in 2016, and the effects on O3 and SOA were evaluated based on the Community Multiscale Air Quality (CMAQ) modeling system. Three LAI satellite datasets of the Global LAnd Surface Satellite (GLASS), the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD15A2H version 6 (MOD15), and the Copernicus Global Land Service (CGLS), as well as three LC satellite datasets of the MODIS MCD12Q1 LC products, the Copernicus Climate Change Service (C3S) LC products, and the CGLS LC products, were used in five parallel experiments (cases: C1–C5). Results show that changing LAI and LC datasets of the model input has an impact on BVOC estimations. BVOC emissions in China ranged from 25.42 to 37.39 Tg in 2016 and were mainly concentrated in central and southeastern China. Changing the LC inputs for the MEGAN model has a more significant difference in BVOC estimates than using different LAI datasets. The combination of C3S LC and GLASS LAI performs better in the CMAQ model, indicating that it is the better choice for BVOC estimations in China. The highest contribution of BVOCs to O3 and SOA can reach 12 ppb and 9.8 µg m−3, respectively. Changing the MEGAN inputs further impacts the concentrations of O3 and SOA, especially changing LC datasets. The relative difference between MCD12Q1 LC and C3S LC is over 52 % and 140 % in O3 and biogenic SOA (BSOA) in central and eastern China. The BSOA difference is mainly attributed to the isoprene SOA (ISOA), a major contributor to BSOA. The relative differences in ISOA between different cases are up to 160 % in eastern China. Therefore, our results suggest that the uncertainties in MEGAN inputs should be fully considered in future O3 and SOA simulations.

Abstract The Hunga‐Tonga Hunga‐Ha'apai volcano underwent a series of large‐magnitude eruptions that generated broad spectra of mechanical waves in the atmosphere. We investigate the spatial and temporal evolutions of fluctuations driven by atmospheric acoustic‐gravity waves (AGWs) and, in particular, the Lamb wave modes in high spatial resolution data sets measured over the Continental United States (CONUS), complemented with data over the Americas and the Pacific. Along with >800 barometer sites, tropospheric observations, and Total Electron Content data from >3,000 receivers, we report detections of volcano‐induced AGWs in mesopause and ionosphere‐thermosphere airglow imagery and Fabry‐Perot interferometry. We also report unique AGW signatures in the ionospheric D‐region, measured using Long‐Range Navigation pulsed low‐frequency transmitter signals. Although we observed fluctuations over a wide range of periods and speeds, we identify Lamb wave modes exhibiting 295–345 m s−1 phase front velocities with correlated spatial variability of their amplitudes from the Earth's surface to the ionosphere. Results suggest that the Lamb wave modes, tracked by our ray‐tracing modeling results, were accompanied by deep fluctuation fields coupled throughout the atmosphere, and were all largely consistent in arrival times with the sequence of eruptions over 8 hr. The ray results also highlight the importance of winds in reducing wave amplitudes at CONUS midlatitudes. The ability to identify and interpret Lamb wave modes and accompanying fluctuations on the basis of arrival times and speeds, despite complexity in their spectra and modulations by the inhomogeneous atmosphere, suggests opportunities for analysis and modeling to understand their signals to constrain features of hazardous events.

The tropospheric concentrations of nitrogen dioxide (NO2) and formaldehyde (HCHO) have high spatio-temporal variability, and in situ observations of these trace gases are still scarce, especially in remote background areas. We made four similar circling journeys of mobile multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements in the Three Rivers' Source region over the Tibetan Plateau in summer (18–30 July) 2021 for the first time. The differential slant column densities (DSCDs) of NO2 and HCHO were retrieved from the measured spectra, with very weak absorptions along the driving routes. The tropospheric NO2 and HCHO vertical column densities (VCDs) were calculated from their DSCDs by the geometric approximation method, and they were further filtered to form reliable data sets by eliminating the influences of sunlight shelters and the vehicle's vibration and bumpiness. The observational data show that the tropospheric NO2 and HCHO VCDs decreased with the increasing altitude of the driving route, whose background levels ± standard deviations were 0.40 ± 1.13×1015 molec. cm−2 for NO2 and 2.27±1.66×1015 molec. cm−2 for HCHO in July 2021 over the Three Rivers' Source region. The NO2 VCDs show similar geographical distribution patterns between the different circling journeys, but the levels of the HCHO VCDs are different between the different circling journeys. The elevated NO2 VCDs along the driving routes usually corresponded to enhanced transport emissions from the towns crossed. However, the spatial distributions of the HCHO VCDs depended significantly on natural and meteorological conditions, such as surface temperature. By comparing TROPOMI satellite products and mobile MAX-DOAS results, we found that TROPOMI NO2 and HCHO VCDs have large positive offsets in the background atmosphere over the main area of the Three Rivers' Source. Our study provides valuable data sets and information of NO2 and HCHO over the Tibetan Plateau, benefitting the scientific community in investigating the spatio-temporal evolution of atmospheric composition in the background atmosphere at high altitudes, validating and improving the satellite products over mountain terrains, and evaluating the model's ability to simulate atmospheric chemistry over the Tibetan Plateau.

Advances in geodetic altimetry instruments are providing more accurate measurements, thus enabling satellite missions to produce useful data for narrow rivers and streams. Altimetry missions produce spatially dense land and water surface elevation (WSE) measurements in remote areas where in situ data are scarce that can be combined with hydraulic and/or hydrodynamic models to simulate WSE and estimate discharge. In this study, we combine ICESat-2 (Ice, Cloud and land Elevation Satellite) land and water surface elevation measurements with a low-parameterized hydraulic calibration to simulate WSE and discharge without the need for surveyed cross-sectional geometry and a rainfall–runoff model. ICESat-2 provides an opportunity to map river cross-sectional geometry very accurately, with an along-track resolution of 0.7 m, using the ATL03 product. These measurements are combined with the inland water product ATL13 to calibrate a steady-state hydraulic model to retrieve unobserved hydraulic parameters such as river depth or the roughness coefficient. The low-parameterized model, together with the assumption of steady-state hydraulics, enables the application of a global search algorithm for a spatially uniform parameter calibration at a manageable computational cost. The model performance is similar to that reported for highly parameterized models, with a root mean square error (RMSE) of around 0.41 m. With the calibrated model, we can calculate the WSE time series at any chainage point at any time for an available satellite pass within the river reach and estimate discharge from WSE. The discharge estimates are validated with in situ measurements at two available gauging stations. In addition, we use the calibrated parameters in a full hydrodynamic model simulation, resulting in a RMSE of 0.59 m for the entire observation period.

ABSTRACT: The objective of this study was to investigate relations between feeding behavior (FB) variables focusing on intake of the basal ration during 3 wk prepartum until 3 wk postpartum, and postpartum onset of luteal activity (OLA) in dairy cows subjected to no (0-d) or a short (30-d) dry period (DP). Feeding behavior of the basal ration intake (concentrate intake excluded) was continuously recorded by computerized feeders for 123 dairy cows and analyzed from 3 wk prepartum to 3 wk postpartum. Cows were subjected to a DP length: 0-d DP (n = 81), or 30-d DP (n = 42). Milk progesterone concentration was determined 3 times per week until 100 DIM to determine OLA, which was classified as early OLA (

By analyzing observations and simulations from the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), we investigated instant and delayed responses of large-scale atmospheric circulations and precipitation to biomass burning (BB) aerosols over the Indochina Peninsula (ICP) in the peak emission of March. The results show that the BB aerosols inhibit precipitation over the ICP in March and promote precipitation from early April to mid April. Specifically, the March BB aerosols over the ICP can induce mid- to lower-tropospheric heating and planetary boundary layer cooling to enhance local atmospheric stability; meanwhile, the perturbation heating can trigger an anomalous low in the lower troposphere to moisten the mid troposphere. However, the convection suppression due to the stabilized atmosphere dominates over the favorable water-vapor condition induced by large-scale circulation responses, leading to overall reduced precipitation over the ICP in March. For the delayed effect, the anomalous low can provide more water vapor as the monsoon advances in early April, although it becomes much weaker without BB aerosols' strong heating. On the other hand, the convective instability above 850 hPa is enhanced by more water vapor, resulting in enhanced precipitation over the ICP, northern South China Sea, and southern China. Thereafter, the condensational latent heating gradually takes over from the BB aerosol radiative heating, acting as the main driver for maintaining the anomalous circulation and thus the delayed effect in mid April.

The development, construction, and first commissioning results of a new scanning microscope installed at the 5-ID Submicron Resolution X-ray Spectroscopy (SRX) beamline at NSLS-II are reported. The developed system utilizes Kirkpatrick–Baez mirrors for X-ray focusing. The instrument is designed to enable spectromicroscopy measurements in 2D and 3D with sub-200 nm spatial resolution. The present paper focuses on the design aspects, optical considerations, and specifics of the sample scanning stage, summarizing some of the initial commissioning results.

Abstract Many studies implicate mitochondrial dysfunction as a key contributor to cell loss in Parkinson disease (PD). Previous analyses of dopaminergic (DAergic) neurons from patients with Lewy-body pathology revealed a deficiency in nuclear-encoded genes for mitochondrial respiration, many of which are targets for the transcription factor estrogen-related receptor gamma (Esrrg/ERRγ). We demonstrate that deletion of ERRγ from DAergic neurons in adult mice was sufficient to cause a levodopa-responsive PD-like phenotype with reductions in mitochondrial gene expression and number, that partial deficiency of ERRγ hastens synuclein-mediated toxicity, and that ERRγ overexpression reduces inclusion load and delays synuclein-mediated cell loss. While ERRγ deletion did not fully recapitulate the transcriptional alterations observed in postmortem tissue, it caused reductions in genes involved in synaptic and mitochondrial function and autophagy. Altogether, these experiments suggest that ERRγ-deficient mice could provide a model for understanding the regulation of transcription in DAergic neurons and that amplifying ERRγ-mediated transcriptional programs should be considered as a strategy to promote DAergic maintenance in PD.

In this paper, we first obtained the temporal-spatial changes of surface subsidence in Ganzhou area based on SBAS-InSAR technology using 24 scenes Sentine-1A images covering the Ganzhou area from 2018 to 2020. Then we studied the surface subsidence characteristics in the study area. Finally, the relationship between surface subsidence and factors such as precipitation, human engineering activities, groundwater extraction, and sediment accumulation were analyzed in Ganzhou area. The results showed that : 80% of the sedimentation rate was −5.4–3.0 mm/a in the study area; serious subsidence areas were mainly located in Ganxian District, which annual average subsidence rate reached −26.4mm/a, and the time series of surface subsidence was accompanied by certain seasonal changes; the seasonal changes in surface subsidence were related to rainfall and groundwater extraction, in addition, the surface subsidence was obviously affected by human engineering activities and river sediment accumulation.

Improved agricultural management plays a vital role in protecting soils from degradation in eastern Africa. Changing practices such as reducing tillage, fertilizer use, or cover crops are expected to enhance soil organic carbon (SOC) storage, with climate change mitigation co-benefits, while increasing crop production. However, the quantification of cropland management effects on agricultural ecosystems remains inadequate in this region. Here, we explored seven management practices and their potential effects on soil carbon (C) pools, nitrogen (N) losses, and crop yields under different climate scenarios, using the dynamic vegetation model LPJ-GUESS. The model performance is evaluated against observations from two long-term maize field trials in western Kenya and reported estimates from published sources. LPJ-GUESS generally produces soil C stocks and maize productivity comparable with measurements and mostly captures the SOC decline under some management practices that is observed in the field experiments. We found that for large parts of Kenya and Ethiopia, an integrated conservation agriculture practice (no-tillage, residue and manure application, and cover crops) increases SOC levels in the long term (+11 % on average), accompanied by increased crop yields (+22 %) in comparison to the conventional management. Planting nitrogen-fixing cover crops in our simulations is also identified as a promising individual practice in eastern Africa to increase soil C storage (+4 %) and crop production (+18 %), with low environmental cost of N losses (+24 %). These management impacts are also sustained in simulations of three future climate pathways. This study highlights the possibilities of conservation agriculture when targeting long-term environmental sustainability and food security in crop ecosystems, particularly for those with poor soil conditions in tropical climates.

Various machine learning methods were attempted in the global mapping of surface ocean partial pressure of CO2 (pCO2) to reduce the uncertainty of the global ocean CO2 sink estimate due to undersampling of pCO2. In previous research, the predictors of pCO2 were usually selected empirically based on theoretic drivers of surface ocean pCO2, and the same combination of predictors was applied in all areas except where there was a lack of coverage. However, the differences between the drivers of surface ocean pCO2 in different regions were not considered. In this work, we combined the stepwise regression algorithm and a feed-forward neural network (FFNN) to select predictors of pCO2 based on the mean absolute error in each of the 11 biogeochemical provinces defined by the self-organizing map (SOM) method. Based on the predictors selected, a monthly global 1∘ × 1∘ surface ocean pCO2 product from January 1992 to August 2019 was constructed. Validation of different combinations of predictors based on the Surface Ocean CO2 Atlas (SOCAT) dataset version 2020 and independent observations from time series stations was carried out. The prediction of pCO2 based on region-specific predictors selected by the stepwise FFNN algorithm was more precise than that based on predictors from previous research. Applying the FFNN size-improving algorithm in each province decreased the mean absolute error (MAE) of the global estimate to 11.32 µatm and the root mean square error (RMSE) to 17.99 µatm. The script file of the stepwise FFNN algorithm and pCO2 product are distributed through the Institute of Oceanology of the Chinese Academy of Sciences Marine Science Data Center (IOCAS, https://doi.org/10.12157/iocas.2021.0022, Zhong, 2021.

Biological nitrogen fixation (BNF) from grain legumes is of significant importance in global agricultural ecosystems. Crops with BNF capability are expected to support the need to increase food production while reducing nitrogen (N) fertilizer input for agricultural sustainability, but quantification of N fixing rates and BNF crop yields remains inadequate on a global scale. Here we incorporate two legume crops (soybean and faba bean) with BNF into a dynamic vegetation model LPJ-GUESS (Lund–Potsdam–Jena General Ecosystem Simulator). The performance of this new implementation is evaluated against observations from a range of water and N management trials. LPJ-GUESS generally captures the observed response to these management practices for legume biomass production, soil N uptake, and N fixation, despite some deviations from observations in some cases. Globally, simulated BNF is dominated by soil moisture and temperature, as well as N fertilizer addition. Annual inputs through BNF are modeled to be 11.6±2.2 Tg N for soybean and 5.6±1.0 Tg N for all pulses, with a total fixation of 17.2±2.9 Tg N yr−1 for all grain legumes during the period 1981–2016 on a global scale. Our estimates show good agreement with some previous statistical estimates but are relatively high compared to some estimates for pulses. This study highlights the importance of accounting for legume N fixation process when modeling C–N interactions in agricultural ecosystems, particularly when it comes to accounting for the combined effects of climate and land-use change on the global terrestrial N cycle.

The uptake of carbonyl sulfide (COS) by terrestrial plants is linked to photosynthetic uptake of CO2 as these gases partly share the same uptake pathway. Applying COS as a photosynthesis tracer in models requires an accurate representation of biosphere COS fluxes, but these models have not been extensively evaluated against field observations of COS fluxes. In this paper, the COS flux as simulated by the Simple Biosphere Model, version 4 (SiB4), is updated with the latest mechanistic insights and evaluated with site observations from different biomes: one evergreen needleleaf forest, two deciduous broadleaf forests, three grasslands, and two crop fields spread over Europe and North America. We improved SiB4 in several ways to improve its representation of COS. To account for the effect of atmospheric COS mole fractions on COS biosphere uptake, we replaced the fixed atmospheric COS mole fraction boundary condition originally used in SiB4 with spatially and temporally varying COS mole fraction fields. Seasonal amplitudes of COS mole fractions are ∼50–200 ppt at the investigated sites with a minimum mole fraction in the late growing season. Incorporating seasonal variability into the model reduces COS uptake rates in the late growing season, allowing better agreement with observations. We also replaced the empirical soil COS uptake model in SiB4 with a mechanistic model that represents both uptake and production of COS in soils, which improves the match with observations over agricultural fields and fertilized grassland soils. The improved version of SiB4 was capable of simulating the diurnal and seasonal variation in COS fluxes in the boreal, temperate, and Mediterranean region. Nonetheless, the daytime vegetation COS flux is underestimated on average by 8±27 %, albeit with large variability across sites. On a global scale, our model modifications decreased the modeled COS terrestrial biosphere sink from 922 Gg S yr−1 in the original SiB4 to 753 Gg S yr−1 in the updated version. The largest decrease in fluxes was driven by lower atmospheric COS mole fractions over regions with high productivity, which highlights the importance of accounting for variations in atmospheric COS mole fractions. The change to a different soil model, on the other hand, had a relatively small effect on the global biosphere COS sink. The secondary role of the modeled soil component in the global COS budget supports the use of COS as a global photosynthesis tracer. A more accurate representation of COS uptake in SiB4 should allow for improved application of atmospheric COS as a tracer of local- to global-scale terrestrial photosynthesis.

Sulfur dioxide (SO2) is a major atmospheric pollutant and precursor of sulfate aerosols, which influences air quality, cloud microphysics, and climate. Therefore, better understanding the conversion of SO2 to sulfate is essential to simulate and predict sulfur compounds more accurately. This study evaluates the effects of in-cloud aqueous-phase chemistry on SO2 oxidation in the Community Earth System Model version 2 (CESM2). We replaced the default parameterized SO2 aqueous-phase reactions with detailed HOx, Fe, N, and carbonate chemistry in cloud droplets and performed a global simulation for 2014–2015. Compared with the observations, the results incorporating detailed cloud aqueous-phase chemistry greatly reduced SO2 overestimation. This overestimation was reduced by 0.1–10 ppbv (parts per billion by volume) in most of Europe, North America, and Asia and more than 10 ppbv in parts of China. The biases in annual simulated SO2 mixing ratios decreased by 46 %, 41 %, and 22 % in Europe, the USA, and China, respectively. Fe chemistry and HOx chemistry contributed more to SO2 oxidation than N chemistry. Higher concentrations of soluble Fe and higher pH values could further enhance the oxidation capacity. This study emphasizes the importance of detailed in-cloud aqueous-phase chemistry for the oxidation of SO2. These mechanisms can improve SO2 simulation in CESM2 and deepen understanding of SO2 oxidation and sulfate formation.

In the aspect of longitudinal beam bunching, the bunching strength can be controlled by the rf cavity phase and voltage. However, these machine parameters are different from those that interact with the beam itself. In order to gain control of the beam-cavity interaction, cavity calibration must be performed. Furthermore, it relies on fitting the beam energy gain versus cavity phase to a calibration function. Under the conventional assumption of relativistic beam conditions, the calibration function is a first harmonic sinusoidal function (a sinusoidal function with a period of 2π). However, this expression is insufficient for a high-voltage bunching cavity. Due to beam acceleration inside the cavity, an energy bias and a second harmonic function should be included to modify the conventional calibration function, even for a relativistic electron beam. In this paper, we will derive this modification and provide a comparison to both the Coherent Electron Cooling Experiment and the impact-t simulation, respectively.

Within a short time after the outbreak of coronavirus disease 2019 (COVID-19) in Wuhan, Hubei, the Chinese government introduced a nationwide lockdown to prevent the spread of the pandemic. The quarantine measures have significantly decreased the anthropogenic activities, thus improving air quality. To study the impacts caused by the lockdown on specific source sectors and regions in the Yangtze River Delta (YRD), the Community Multiscale Air Quality (CMAQ) model was used to investigate the changes in source contributions to fine particulate matter (PM2.5) from 23 January to 28 February 2020, based on different emission control cases. Compared to case 1 (without emission reductions), the total PM2.5 mass for case 2 (with emission reductions) decreased by more than 20 % over the entire YRD, and the reduction ratios of its components were 15 %, 16 %, 20 %, 43 %, 34 %, and 35 % in primary organic aerosol (POA), elemental carbon (EC), sulfate, nitrate, ammonium, and secondary organic aerosol (SOA), respectively. The source apportionment results showed that PM2.5 concentrations from transportation decreased by 40 %, while PM2.5 concentrations from the residential and power sectors decreased by less than 10 % due to the lockdown. Although all sources decreased, the relative contribution changed differently. Contributions from the residential sector increased by more than 10 % to 35 %, while those in the industrial sector decreased by 33 %. Considering regional transport, the total PM2.5 mass of all regions decreased 20 %–30 % in the YRD, with the largest decreased value of 5.0 µg m−3 in Henan, Hebei, Beijing, and Tianjin (Ha-BTH). In Shanghai, the lower contributions from local emissions and regional transmission (mainly Shandong and Ha-BTH) led to the reduced PM2.5. This study suggests adjustments of control measures for various sources and regions.

Effects of the El Niño–Southern Oscillation (ENSO) on the interannual variability in spring aerosols over East Asia are investigated using the Modern Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) reanalysis aerosol data. Results show that the ENSO has a crucial effect on the spring aerosols over mainland South East Asia, southern China, and the ocean south of Japan. The above-normal (below-normal) aerosols are found over these regions during the ensuing spring of El Niño (La Niña). In contrast to the local aerosol diffusion in winter, the ENSO affects East Asian aerosols in the following spring mainly via the modulation of upstream aerosol generation and transport processes. The underlying physical mechanism is that during the ensuing spring of El Niño (La Niña), the dry (wet) air and reduced (enhanced) precipitation are beneficial for the increase (reduction) in biomass burning activities over northern mainland South East Asia, resulting in more (fewer) carbonaceous aerosol emissions. On the other hand, the anomalous anticyclone (cyclone) over the north-western Pacific (WNP) associated with El Niño (La Niña) enhances (weakens) the low-level south-westerly wind from northern mainland South East Asia to southern Japan, which transports more (less) carbonaceous aerosol downstream. Anomalous precipitation plays a role in reducing aerosols over the source region, but its washout effect over the downstream region is limited. The ENSO's impact on the ensuing spring aerosols is mainly attributed to the eastern Pacific ENSO rather than the central Pacific ENSO.

Carbonyl sulfide (COS) has the potential to be used as a climate diagnostic due to its close coupling to the biospheric uptake of CO2 and its role in the formation of stratospheric aerosol. The current understanding of the COS budget, however, lacks COS sources, which have previously been allocated to the tropical ocean. This paper presents a first attempt at global inverse modelling of COS within the 4-dimensional variational data-assimilation system of the TM5 chemistry transport model (TM5-4DVAR) and a comparison of the results with various COS observations. We focus on the global COS budget, including COS production from its precursors carbon disulfide (CS2) and dimethyl sulfide (DMS). To this end, we implemented COS uptake by soil and vegetation from an updated biosphere model (Simple Biosphere Model – SiB4). In the calculation of these fluxes, a fixed atmospheric mole fraction of 500 pmol mol−1 was assumed. We also used new inventories for anthropogenic and biomass burning emissions. The model framework is capable of closing the COS budget by optimizing for missing emissions using NOAA observations in the period 2000–2012. The addition of 432 Gg a−1 (as S equivalents) of COS is required to obtain a good fit with NOAA observations. This missing source shows few year-to-year variations but considerable seasonal variations. We found that the missing sources are likely located in the tropical regions, and an overestimated biospheric sink in the tropics cannot be ruled out due to missing observations in the tropical continental boundary layer. Moreover, high latitudes in the Northern Hemisphere require extra COS uptake or reduced emissions. HIPPO (HIAPER Pole-to-Pole Observations) aircraft observations, NOAA airborne profiles from an ongoing monitoring programme and several satellite data sources are used to evaluate the optimized model results. This evaluation indicates that COS mole fractions in the free troposphere remain underestimated after optimization. Assimilation of HIPPO observations slightly improves this model bias, which implies that additional observations are urgently required to constrain sources and sinks of COS. We finally find that the biosphere flux dependency on the surface COS mole fraction (which was not accounted for in this study) may substantially lower the fluxes of the SiB4 biosphere model over strong-uptake regions. Using COS mole fractions from our inversion, the prior biosphere flux reduces from 1053 to 851 Gg a−1, which is closer to 738 Gg a−1 as was found by Berry et al. (2013). In planned further studies we will implement this biosphere dependency and additionally assimilate satellite data with the aim of better separating the role of the oceans and the biosphere in the global COS budget.

To mitigate the impacts of the pandemic of coronavirus disease 2019 (COVID-19), the Indian government implemented lockdown measures on 24 March 2020, which prohibited unnecessary anthropogenic activities, thus leading to a significant reduction in emissions. To investigate the impacts of this lockdown measure on air quality in India, we used the Community Multi-Scale Air Quality (CMAQ) model to estimate the changes of key air pollutants. From pre-lockdown to lockdown periods, improved air quality is observed in India, indicated by the lower key pollutant levels such as PM2.5 (−26 %), maximum daily 8 h average ozone (MDA8 O3) (−11 %), NO2 (−50 %), and SO2 (−14 %). In addition, changes in these pollutants show distinct spatial variations with the more important decrease in northern and western India. During the lockdown, our results illustrate that such emission reductions play a positive role in the improvement of air quality. Significant reductions of PM2.5 concentration and its major components are predicted, especially for secondary inorganic aerosols that are up to 92 %, 57 %, and 79 % for nitrate (NO3-), sulfate (SO42-), and ammonium (NH4+), respectively. On average, the MDA8 O3 also decreases 15 % during the lockdown period although it increases slightly in some VOC-limited urban locations, which is mainly due to the more significant reduction of NOx than VOCs. More aggressive and localized emission control strategies should be implemented in India to mitigate air pollution in the future.

Atmospheric submicrometer aerosols have a great effect on air quality and human health, while their formation and evolution processes are still not fully understood. Herein, the crucial role of atmospheric oxidation capacity, as characterized by OH exposure dose in the formation and evolution of secondary submicrometer aerosols, was systematically investigated based on a highly time-resolved chemical characterization of PM1 in a southern suburb of Beijing in summertime from 25 July to 21 August 2019. The averaged concentration of PM1 was 19.3 ± 11.3 µg m−3, and nearly half (48.3 %) of the mass was organic aerosols (OAs) during the observation period. The equivalent photochemical age (ta) estimated from the ratios of toluene to benzene was applied to characterize the OH exposure dose of the air mass, in which an observation period with the similar sources and minimal influence of fresh emission was adopted. The relationships of non-refractory PM1 species, OA factors (i.e., one hydrocarbon-like and three oxygenated organic aerosol factors) and elemental compositions (e.g., H∕C, O∕C, N∕C, S∕C, OM∕OC, and OSc) to ta were analyzed in detail. It was found that higher PM1 concentration accompanied longer ta, with an average increase rate of 0.8 µgm-3h-1. Meanwhile, the formation of sulfate and more oxidized oxygenated OA were most sensitive to the increase in ta, and their contributions to PM1 were enhanced from 22 % to 28 % and from 29 % to 48 %, respectively, as ta increased. In addition, OSc and the ratios of O∕C and OM∕OC increased with the increase in ta. These results indicated that photochemical aging is a key factor leading to the evolution of OA and the increase in PM1 in summertime.

Ocean acidification (OA), which is a major environmental change caused by increasing atmospheric CO2, has considerable influences on marine phytoplankton. But few studies have investigated interactions of OA and seasonal changes in temperature and photoperiod on marine diatoms. In the present study, a marine diatom Skeletonema costatum was cultured under two different CO2 levels (LC, 400 µatm; HC, 1000 µatm) and three different combinations of temperature and photoperiod length (8:16 L:D with 5 ∘C, 12:12 L:D with 15 ∘C, 16:8 L:D with 25 ∘C), simulating different seasons in typical temperate oceans, to investigate the combined effects of these factors. The results showed that specific growth rate of S. costatum increased with increasing temperature and day length. However, OA showed contrasting effects on growth and photosynthesis under different combinations of temperature and day length: while positive effects of OA were observed under spring and autumn conditions, it significantly decreased growth (11 %) and photosynthesis (21 %) in winter. In addition, OA alleviated the negative effect of low temperature and short day length on the abundance of RbcL and key photosystem II (PSII) proteins (D1 and D2). These data indicated that future ocean acidification may show differential effects on diatoms in different clusters of other factors.

Abstract High brightness, high charge electron beams are critical for a number of advanced accelerator applications. The initial emittance of the electron beam, which is determined by the mean transverse energy (MTE) and laser spot size, is one of the most important parameters determining the beam quality. The bialkali photocathodes illuminated by a visible laser have the advantages of high quantum efficiency (QE) and low MTE. Furthermore, Superconducting Radio Frequency (SRF) guns can operate in the continuous wave (CW) mode at high accelerating gradients, e.g. with significant reduction of the laser spot size at the photocathode. Combining the bialkali photocathode with the SRF gun enables generation of high charge, high brightness, and possibly high average current electron beams. However, integrating the high QE semiconductor photocathode into the SRF guns has been challenging. In this article, we report on the development of bialkali photocathodes for successful operation in the SRF gun with months-long lifetime while delivering CW beams with nano-coulomb charge per bunch. This achievement opens a new era for high charge, high brightness CW electron beams.

The second Cabauw Intercomparison of Nitrogen Dioxide measuring Instruments (CINDI-2) took place in Cabauw (the Netherlands) in September 2016 with the aim of assessing the consistency of multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements of tropospheric species (NO2, HCHO, O3, HONO, CHOCHO and O4). This was achieved through the coordinated operation of 36 spectrometers operated by 24 groups from all over the world, together with a wide range of supporting reference observations (in situ analysers, balloon sondes, lidars, long-path DOAS, direct-sun DOAS, Sun photometer and meteorological instruments). In the presented study, the retrieved CINDI-2 MAX-DOAS trace gas (NO2, HCHO) and aerosol vertical profiles of 15 participating groups using different inversion algorithms are compared and validated against the colocated supporting observations, with the focus on aerosol optical thicknesses (AOTs), trace gas vertical column densities (VCDs) and trace gas surface concentrations. The algorithms are based on three different techniques: six use the optimal estimation method, two use a parameterized approach and one algorithm relies on simplified radiative transport assumptions and analytical calculations. To assess the agreement among the inversion algorithms independent of inconsistencies in the trace gas slant column density acquisition, participants applied their inversion to a common set of slant columns. Further, important settings like the retrieval grid, profiles of O3, temperature and pressure as well as aerosol optical properties and a priori assumptions (for optimal estimation algorithms) have been prescribed to reduce possible sources of discrepancies. The profiling results were found to be in good qualitative agreement: most participants obtained the same features in the retrieved vertical trace gas and aerosol distributions; however, these are sometimes at different altitudes and of different magnitudes. Under clear-sky conditions, the root-mean-square differences (RMSDs) among the results of individual participants are in the range of 0.01–0.1 for AOTs, (1.5–15) ×1014molec.cm-2 for trace gas (NO2, HCHO) VCDs and (0.3–8)×1010molec.cm-3 for trace gas surface concentrations. These values compare to approximate average optical thicknesses of 0.3, trace gas vertical columns of 90×1014molec.cm-2 and trace gas surface concentrations of 11×1010molec.cm-3 observed over the campaign period. The discrepancies originate from differences in the applied techniques, the exact implementation of the algorithms and the user-defined settings that were not prescribed. For the comparison against supporting observations, the RMSDs increase to a range of 0.02–0.2 against AOTs from the Sun photometer, (11–55)×1014molec.cm-2 against trace gas VCDs from direct-sun DOAS observations and (0.8–9)×1010molec.cm-3 against surface concentrations from the long-path DOAS instrument. This increase in RMSDs is most likely caused by uncertainties in the supporting data, spatiotemporal mismatch among the observations and simplified assumptions particularly on aerosol optical properties made for the MAX-DOAS retrieval. As a side investigation, the comparison was repeated with the participants retrieving profiles from their own differential slant column densities (dSCDs) acquired during the campaign. In this case, the consistency among the participants degrades by about 30 % for AOTs, by 180 % (40 %) for HCHO (NO2) VCDs and by 90 % (20 %) for HCHO (NO2) surface concentrations. In former publications and also during this comparison study, it was found that MAX-DOAS vertically integrated aerosol extinction coefficient profiles systematically underestimate the AOT observed by the Sun photometer. For the first time, it is quantitatively shown that for optimal estimation algorithms this can be largely explained and compensated by considering biases arising from the reduced sensitivity of MAX-DOAS observations to higher altitudes and associated a priori assumptions.

High-resolution sea ice modeling is becoming widely available for both operational forecasts and climate studies. In traditional Eulerian grid-based models, small-scale sea ice kinematics represent the most prominent feature of high-resolution simulations, and with rheology models such as viscous–plastic (VP) and Maxwell elasto-brittle (MEB), sea ice models are able to reproduce multi-fractal sea ice deformation and linear kinematic features that are seen in high-resolution observational datasets. In this study, we carry out modeling of sea ice with multiple grid resolutions by using the Community Earth System Model (CESM) and a grid hierarchy (22, 7.3, and 2.4 km grid stepping in the Arctic). By using atmospherically forced experiments, we simulate consistent sea ice climatology across the three resolutions. Furthermore, the model reproduces reasonable sea ice kinematics, including multi-fractal spatial scaling of sea ice deformation that partially depends on atmospheric circulation patterns and forcings. By using high-resolution runs as references, we evaluate the model's effective resolution with respect to the statistics of sea ice kinematics. Specifically, we find the spatial scale at which the probability density function (PDF) of the scaled sea ice deformation rate of low-resolution runs matches that of high-resolution runs. This critical scale is treated as the effective resolution of the coarse-resolution grid, which is estimated to be about 6 to 7 times the grid's native resolution. We show that in our model, the convergence of the elastic–viscous–plastic (EVP) rheology scheme plays an important role in reproducing reasonable kinematics statistics and, more strikingly, simulates systematically thinner sea ice than the standard, non-convergent experiments in landfast ice regions of the Canadian Arctic Archipelago. Given the wide adoption of EVP and subcycling settings in current models, it highlights the importance of EVP convergence, especially for climate studies and projections. The new grids and the model integration in CESM are openly provided for public use.

The hydroxyl radical (OH) determines the capability of atmospheric self-cleansing and is one of the significant oxidants in atmospheric photochemistry reactions. Global OH has been monitored by satellites with the traditional limb mode in the past decades. This observed mode can achieve the acquisition of high-resolution vertical OH data but cannot obtain enough horizontal OH data for inverting high-precision OH concentrations because OH has a high reactivity that makes OH concentrations extremely low and distributions complicated. The double spatial heterodyne spectrometer (DSHS) is designed to obtain higher-resolution and more detailed OH data. This sensor can measure OH by the three-dimensional limb mode to obtain comprehensive OH data in the atmosphere. Here we propose a new tomographic retrieval algorithm based on the simulated observation data because the DSHS will work officially on the orbit in the future. We build up an accurate forward model. The main part of it is the SCIATRAN radiative transfer model which is modified according to the radiation transmission theory. The error in results obtained by the forward model is ±44.30 % in the lower atmosphere such as at a 21 km height and decreases gradually until the limit of observation altitude. We also construct the tomographic retrieval algorithm of which the core is a lookup table method. A tomographic-observation database is built up through the atmospheric model, the spatial information (the position of the target area and satellite position), the date parameters, the observation geometries, OH concentrations, and simulated observation data. The OH concentrations can be found from it directly. If there are no corresponding query conditions in the tomographic-observation database, the cubic spline interpolation is used to obtain the OH concentrations. The inversion results are given, and the errors in them increase as the altitudes rise until about a 41 km height then start to decrease. The errors in the inversion results reach the maximum of about ±25.03 % at the 41 km height and decrease to ±8.09 % at the limited observation height. They are also small in the lower atmosphere at ±12.96 % at 21 km. In summary, the tomographic retrieval algorithm can obtain more accurate OH concentrations even in the lower atmosphere where the OH data are not high quality and avoids the setting of initial guess values for solving the iteration problems. Our research not only provides support for the scientific theory of the construction of the DSHS but also gives a new retrieval algorithm idea for other radicals.

Land surface temperature (LST) plays an important role in the research of climate change and various land surface processes. Before 2000, global LST products with relatively high temporal and spatial resolutions are scarce, despite a variety of operational satellite LST products. In this study, a global 0.05∘×0.05∘ historical LST product is generated from NOAA advanced very-high-resolution radiometer (AVHRR) data (1981–2000), which includes three data layers: (1) instantaneous LST, a product generated by integrating several split-window algorithms with a random forest (RF-SWA); (2) orbital-drift-corrected (ODC) LST, a drift-corrected version of RF-SWA LST; and (3) monthly averages of ODC LST. For an assumed maximum uncertainty in emissivity and column water vapor content of 0.04 and 1.0 g cm−2, respectively, evaluated against the simulation dataset, the RF-SWA method has a mean bias error (MBE) of less than 0.10 K and a standard deviation (SD) of 1.10 K. To compensate for the influence of orbital drift on LST, the retrieved RF-SWA LST was normalized with an improved ODC method. The RF-SWA LST were validated with in situ LST from Surface Radiation Budget (SURFRAD) sites and water temperatures obtained from the National Data Buoy Center (NDBC). Against the in situ LST, the RF-SWA LST has a MBE of 0.03 K with a range of −1.59–2.71 K, and SD is 1.18 K with a range of 0.84–2.76 K. Since water temperature only changes slowly, the validation of ODC LST was limited to SURFRAD sites, for which the MBE is 0.54 K with a range of −1.05 to 3.01 K and SD is 3.57 K with a range of 2.34 to 3.69 K, indicating good product accuracy. As global historical datasets, the new AVHRR LST products are useful for filling the gaps in long-term LST data. Furthermore, the new LST products can be used as input to related land surface models and environmental applications. Furthermore, in support of the scientific research community, the datasets are freely available at https://doi.org/10.5281/zenodo.3934354 for RF-SWA LST (Ma et al., 2020a), https://doi.org/10.5281/zenodo.3936627 for ODC LST (Ma et al., 2020c), and https://doi.org/10.5281/zenodo.3936641 for monthly averaged LST (Ma et al., 2020b).

Multi-axis differential optical absorption spectroscopy (MAX-DOAS) and direct sun NO2 vertical column network data are used to investigate the accuracy of tropospheric NO2 column measurements of the GOME-2 instrument on the MetOp-A satellite platform and the OMI instrument on Aura. The study is based on 23 MAX-DOAS and 16 direct sun instruments at stations distributed worldwide. A method to quantify and correct for horizontal dilution effects in heterogeneous NO2 field conditions is proposed. After systematic application of this correction to urban sites, satellite measurements are found to present smaller biases compared to ground-based reference data in almost all cases. We investigate the seasonal dependence of the validation results as well as the impact of using different approaches to select satellite ground pixels in coincidence with ground-based data. In optimal comparison conditions (satellite pixels containing the station) the median bias between satellite tropospheric NO2 column measurements and the ensemble of MAX-DOAS and direct sun measurements is found to be significant and equal to −34 % for GOME-2A and −24 % for OMI. These biases are further reduced to −24 % and −18 % respectively, after application of the dilution correction. Comparisons with the QA4ECV satellite product for both GOME-2A and OMI are also performed, showing less scatter but also a slightly larger median tropospheric NO2 column bias with respect to the ensemble of MAX-DOAS and direct sun measurements.

Background: Very few studies have assessed the role of a clinical pharmacist in women with gestational diabetes mellitus (GDM). To improve pharmaceutical care, we explored a method to improve the control of blood glucose and perinatal outcomes in females with GDM through the application of a diabetes management system. Methods: A randomized controlled trial was conducted from October 2017 to October 2018 for 200 outpatients with GDM. In the study, a diabetes management system with pharmaceutical care was used for the intervention group. The clinical outcomes of all patients were recorded at the end of delivery. Results: From one sample of 200 patients, 169 finished the research. Compared with the control group, patients in the intervention group manifested greater reductions in fasting plasma glucose (5.22 ± 0.37 vs. 6.05 ± 1.06 mmol/L; P = 0.018), 2 h postprandial plasma glucose (6.66 ± 0.57 vs. 9.69 ± 1.58 mmol/L; P = 0.00), and glycated hemoglobin A1c corrected values (1.02 ± 0.12 vs. 1.16 ± 0.22; P = 0.023). Moreover, the rate of polyhydramnios was significantly lower in the intervention group than in the control group (0% vs. 10.59%; P = 0.003) as well as significantly fewer macrosomia in the intervention group (7.14% vs. 18.82%; P = 0.038). Conclusions: Using a diabetes management system, clinical pharmacists can improve the control of blood glucose and perinatal results in GDM females. With a diabetes management system, the comprehensive management of GDM is a new model for pharmaceutical care in the future.

We carried out 19 city-circle-around car multi-axis differential optical absorption spectroscopy (MAX-DOAS) experiments on the 6th Ring Road of Beijing in January, September, and October 2014. The tropospheric vertical column densities (VCDs) of NO2 were retrieved from measured spectra by the MAX-DOAS technique and used to estimate the emissions of NOx (≡NO+NO2) from urban Beijing during the experimental periods. The offline LAPS-WRF-CMAQ model system was used to simulate the wind fields by assimilation of observational data and calculate the NO2-to-NOx concentration ratios, both of which are also needed for the estimation of NOx emissions. The NOx emissions in urban Beijing for the different months derived from the car MAX-DOAS measurements in this study were compared to the multi-resolution emission inventory in China for 2012 (MEIC 2012). Our car MAX-DOAS measurements showed higher NO2 VCD in January than in the other two months. The wind field had obvious impacts on the spatial distribution of NO2 VCD, with the mean NO2 VCD along the 6th Ring Road typically being higher under the southerly wind than under the northerly wind. In addition to the seasonal difference, the journey-to-journey variations of estimated NOx emission rates (ENOx) were large even within the same month, mainly due to uncertainties in the calculations of wind speed, the ratio of NO2 and NOx concentration, and the decay rate of NOx from the emission sources to the measured positions under different meteorological conditions. The ranges of ENOx during the heating and non-heating periods were 22.6×1025 to 31.3×1025 and 9.6×1025 to 12.0×1025 molec. s−1, respectively. The average ENOx values in the heating and non-heating periods were 26.9±6.1×1025 molec. s−1 and 11.0±1.2×1025 molec. s−1, respectively. The uncertainty range of ENOx was 20 %–52 %. The monthly emission rates from MEIC 2012 are found to be lower than the estimated ENOx, particularly in January. Our results provide important information and datasets for the validation of satellite products and also show how car MAX-DOAS measurements can be used effectively for dynamic monitoring and updating of the NOx emissions from megacities such as Beijing.

We present the inter-comparison of delta slant column densities (SCDs) and vertical profiles of nitrous acid (HONO) derived from measurements of different multi-axis differential optical absorption spectroscopy (MAX-DOAS) instruments and using different inversion algorithms during the Second Cabauw Inter-comparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) in September 2016 at Cabauw, the Netherlands (51.97∘ N, 4.93∘ E). The HONO vertical profiles, vertical column densities (VCDs), and near-surface volume mixing ratios are compared between different MAX-DOAS instruments and profile inversion algorithms for the first time. Systematic and random discrepancies of the HONO results are derived from the comparisons of all data sets against their median values. Systematic discrepancies of HONO delta SCDs are observed in the range of ±0.3×1015 molec. cm−2, which is half of the typical random discrepancy of 0.6×1015 molec. cm−2. For a typical high HONO delta SCD of 2×1015 molec. cm−2, the relative systematic and random discrepancies are about 15 % and 30 %, respectively. The inter-comparison of HONO profiles shows that both systematic and random discrepancies of HONO VCDs and near-surface volume mixing ratios (VMRs) are mostly in the range of ∼±0.5×1014 molec. cm−2 and ∼±0.1 ppb (typically ∼20 %). Further we find that the discrepancies of the retrieved HONO profiles are dominated by discrepancies of the HONO delta SCDs. The profile retrievals only contribute to the discrepancies of the HONO profiles by ∼5 %. However, some data sets with substantially larger discrepancies than the typical values indicate that inappropriate implementations of profile inversion algorithms and configurations of radiative transfer models in the profile retrievals can also be an important uncertainty source. In addition, estimations of measurement uncertainties of HONO dSCDs, which can significantly impact profile retrievals using the optimal estimation method, need to consider not only DOAS fit errors, but also atmospheric variability, especially for an instrument with a DOAS fit error lower than ∼3×1014 molec. cm−2. The MAX-DOAS results during the CINDI-2 campaign indicate that the peak HONO levels (e.g. near-surface VMRs of ∼0.4 ppb) often appeared in the early morning and below 0.2 km. The near-surface VMRs retrieved from the MAX-DOAS observations are compared with those measured using a co-located long-path DOAS instrument. The systematic differences are smaller than 0.15 and 0.07 ppb during early morning and around noon, respectively. Since true HONO values at high altitudes are not known in the absence of real measurements, in order to evaluate the abilities of profile inversion algorithms to respond to different HONO profile shapes, we performed sensitivity studies using synthetic HONO delta SCDs simulated by a radiative transfer model with assumed HONO profiles. The tests indicate that the profile inversion algorithms based on the optimal estimation method with proper configurations can reproduce the different HONO profile shapes well. Therefore we conclude that the features of HONO accumulated near the surface derived from MAX-DOAS measurements are expected to represent the ambient HONO profiles well.

Mt. Waliguan Observatory (WLG) is a World Meteorological Organization (WMO) Global Atmosphere Watch (GAW) global baseline station in China. WLG is located at the northeastern part of the Tibetan Plateau (36∘17′ N, 100∘54′ E, 3816 m a.s.l.) and is representative of the pristine atmosphere over the Eurasian continent. We made long-term ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements at WLG during the period 2012–2015. In this study, we retrieve the differential slant column densities (dSCDs) and estimate the tropospheric background mixing ratios of different trace gases, including NO2, SO2, HCHO, and BrO, using the measured spectra at WLG. Averaging of 10 original spectra is found to be an “optimum option” for reducing both the statistical error of the spectral retrieval and systematic errors in the analysis. The dSCDs of NO2, SO2, HCHO, and BrO under clear-sky and low-aerosol-load conditions are extracted from measured spectra at different elevation angles at WLG. By performing radiative transfer simulations with the model TRACY-2, we establish approximate relationships between the trace gas dSCDs at 1∘ elevation angle and the corresponding average tropospheric background volume mixing ratios. Mixing ratios of these trace gases in the lower troposphere over WLG are estimated to be in a range of about 7 ppt (January) to 100 ppt (May) for NO2, below 0.5 ppb for SO2, between 0.4 and 0.9 ppb for HCHO, and lower than 0.3 ppt for BrO. The chemical box model simulations constrained by the NO2 concentration from our MAX-DOAS measurements show that there is a little net ozone loss (−0.8 ppb d−1) for the free-tropospheric conditions and a little net ozone production (0.3 ppb d−1) for the boundary layer conditions over WLG during summertime. Our study provides valuable information and data sets for further investigating tropospheric chemistry in the background atmosphere and its links to anthropogenic activities.

This paper is focused on the field of the skeletonization of the binary image. Skeletonization makes it possible to represent a binary image in the form of many thin lines, the relative position, sizes and shape of which adequately describe the size, shape and orientation in space of the corresponding image areas. Skeletonization has many variety methods. Iterative parallel algorithms provide high quality skeletons. They can be implemented using one or more sub-iterations. In each iteration, redundant pixels, the neighborhoods of which meet certain conditions, are removed layer by layer along the contour and finally they leave only the skeleton. Many one-sub-iterations algorithms are characterized by a breakdown in connectivity and the formation of excess skeleton fragments. The highest-quality skeletons are formed by the well-known single-iteration OPTA algorithm, which based on 18 binary masks, but it is sensitive to contour noise and has a high computational complexity. The Zhang and Suen two-iteration algorithm (ZS), which is based on 6 logical conditions, is widely used due to its relative simplicity. But it suffers from the problem of the blurs of the diagonal lines with a thickness of 2 pixels and the lost of the square which size is 2×2 pixels. Besides, both algorithms mentioned above do not achieve the unit pixel thickness of the skeleton lines (many non-node pixels have more than two neighbors). Mathematical model and OPCA (One-Pass Combination Algorithm) algorithm which is based on a combination and simplification of single-iterative OPTA and two-iterative ZS are proposed for constructing extremely thin bound skeletons of binary images with low computational complexity. These model and algorithm also made it possible to accelerate the speed of skeletonization, to enhance recoverability of the original image on the skeleton and to reduce the redundancy of the bonds of the skeleton elements.

In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 d during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, the Netherlands (51.97∘ N, 4.93∘ E). We report on the outcome of the formal semi-blind intercomparison exercise, which was held under the umbrella of the Network for the Detection of Atmospheric Composition Change (NDACC) and the European Space Agency (ESA). The three major goals of CINDI-2 were (1) to characterise and better understand the differences between a large number of multi-axis differential optical absorption spectroscopy (MAX-DOAS) and zenith-sky DOAS instruments and analysis methods, (2) to define a robust methodology for performance assessment of all participating instruments, and (3) to contribute to a harmonisation of the measurement settings and retrieval methods. This, in turn, creates the capability to produce consistent high-quality ground-based data sets, which are an essential requirement to generate reliable long-term measurement time series suitable for trend analysis and satellite data validation. The data products investigated during the semi-blind intercomparison are slant columns of nitrogen dioxide (NO2), the oxygen collision complex (O4) and ozone (O3) measured in the UV and visible wavelength region, formaldehyde (HCHO) in the UV spectral region, and NO2 in an additional (smaller) wavelength range in the visible region. The campaign design and implementation processes are discussed in detail including the measurement protocol, calibration procedures and slant column retrieval settings. Strong emphasis was put on the careful alignment and synchronisation of the measurement systems, resulting in a unique set of measurements made under highly comparable air mass conditions. The CINDI-2 data sets were investigated using a regression analysis of the slant columns measured by each instrument and for each of the target data products. The slope and intercept of the regression analysis respectively quantify the mean systematic bias and offset of the individual data sets against the selected reference (which is obtained from the median of either all data sets or a subset), and the rms error provides an estimate of the measurement noise or dispersion. These three criteria are examined and for each of the parameters and each of the data products, performance thresholds are set and applied to all the measurements. The approach presented here has been developed based on heritage from previous intercomparison exercises. It introduces a quantitative assessment of the consistency between all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques.

We present different methods for in-field elevation calibration of MAX-DOAS (Multi AXis Differential Optical Absorption Spectroscopy) instruments that were applied and inter-compared during the second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2). One necessary prerequisite of consistent MAX-DOAS retrievals is a precise and accurate calibration of the elevation angles of the different measuring systems. Therefore, different methods for this calibration were applied to several instruments during the campaign, and the results were inter-compared. This work first introduces and explains the different methods, namely far- and near-lamp measurements, white-stripe scans, horizon scans and sun scans, using data and results for only one (mainly the Max Planck Institute for Chemistry) instrument. In the second part, the far-lamp measurements and the horizon scans are examined for all participating groups. Here, the results for both methods are first inter-compared for the different instruments; secondly, the two methods are compared amongst each other. All methods turned out to be well-suited for the calibration of the elevation angles of MAX-DOAS systems, with each of them having individual advantages and drawbacks. Considering the results of this study, the systematic uncertainties of the methods can be estimated as ±0.05∘ for the far-lamp measurements and the sun scans, ±0.25∘ for the horizon scans, and around ±0.1∘ for the white-stripe and near-lamp measurements. When comparing the results of far-lamp and horizon-scan measurements, a spread of around 0.9∘ in the elevation calibrations is found between the participating instruments for both methods. This spread is of the order of a typical field of view (FOV) of a MAX-DOAS instrument and therefore affecting the retrieval results. Further, consistent (wavelength dependent) offsets of 0.32∘ and 0.40∘ between far-lamp measurements and horizon scans are found, which can be explained by the fact that, despite the flat topography around the measurement site, obstacles such as trees might mark the visible horizon during daytime. The observed wavelength dependence can be explained by surface albedo effects. Lastly, the results are discussed and recommendations for future campaigns are given.

The qualitative analysis of human landscape vulnerability is widely recognized, but quantitative analysis needs a lot of manpower, material resources as well as time to carry out the social observation. Based on remote sensing and spatial data, quantitative analysis of human landscape vulnerability will change this situation. This paper put forward a vulnerability evaluation model for change detection with remote sensing time series images and spatial tourism data. It is not only a quickly analysis tool which spans from the earth observation to the social observation for quantitative evaluation, but also an assistant tool for decision-making from change detection analysis to trend analysis.The vulnerability evaluation model of Jiuzhaigou Tibetan human landscape highlights the vulnerability of the whole region has increased significantly. The good structure ratios of bio-abundance are the basis of the human landscape protection, but the activities of ice and snow areas may be a natural factor for the migration of native along the tour roads in the valley from hillsides. The impact of tourism activities is far less than the natural environment. But tourism activities have inevitably affected the human landscape protection, and its negative index benefit is almost three times as much as the positive index benefit of protection measures. Especially, with the change of production and lifestyle of native brought by tourism activities, the human landscape is gradually disappearing. Further development of tourism activities will also extend the impact to the Balance Zone. It is urgent to reconstruct the current management model of human landscape.