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The spatio-temporal data of intelligent and connected vehicles (ICVs) represent crucial surveying and mapping data generated by these vehicles. The massive collection, processing, and aggregation of such data pose potential security risks to geographic information security and even national security. This paper analyzes the significance of spatio-temporal data in ICVs and provides extensive application examples. By comparing the current research status in the United States, the European Union, Japan, it elaborates in detail on China's management status and summarizes practical experience in multiple advanced cities within the country for safety management.Incorporating the current domestic processes of spatio-temporal data generation, transmission, and processing, the paper assesses data security risk,network security risk, and system security risk. Furthermore, this paper proposes recommendations on how to establish spatio-temporal data security management system from various levels, including government, enterprises, and society, to effectively address potential and existing security risks.

Accurate and timely global evapotranspiration (ET) data are crucial for agriculture, water resource management, and drought forecasting. Although numerous satellite-based ET products are available, few offer near-real-time data. For instance, products like NASA's ECOsystem Spaceborne Thermal Radiometer Experiment mounted on the International Space Station (ECOSTRESS) and MOD16 face challenges such as uneven coverage and delays exceeding 1 week in data availability. In this study, we refined the Variation of the Standard Evapotranspiration Algorithm (VISEA) by fully integrating satellite-based data, e.g., European Centre for Medium-Range Weather Forecasts ERA5-Land shortwave radiation (which includes satellite remote sensing data within its assimilation system) and MODIS land surface data (which include surface reflectance, temperature and/or emissivity, land cover, vegetation indices, and albedo as inputs). This enables VISEA to provide near-real-time global daily ET estimates with a maximum delay of 1 week at a resolution of 0.05°. Its accuracy was assessed globally using observation data from 149 flux towers across 12 land cover types and comparing them with five other satellite-based ET products and Global Precipitation Climatology Centre (GPCC) data. The results indicate that VISEA provides accurate ET estimates that are comparable to existing products, achieving a mean correlation coefficient (R) of about 0.6 and an RMSE of 1.4 mm d−1. Furthermore, we demonstrated VISEA's utility in drought monitoring during a drought event in the Yangtze River basin in 2022 in which ET changes correlated with precipitation. The near-real-time capability of VISEA is, thus, especially valuable in meteorological and hydrological applications for coordinating drought relief efforts. The VISEA ET dataset is available at https://doi.org/10.11888/Terre.tpdc.300782 (Huang, 2023a).

The total freeboard, which is the ice layer above water level and includes the snow thickness, is needed to retrieve the ice thickness and ice surface topography. Single-pass interferometric synthetic aperture radar (InSAR) allows for the generation of digital elevation models (DEMs) over the drifting sea ice. However, accurate sea ice DEMs (i.e., the total freeboard) derived from InSAR are impeded due to variation in the penetration of the radar signals into the snow and ice layers. This research introduces a novel methodology for retrieving sea ice DEMs using dual-polarization interferometric SAR images, considering the variation in radar penetration bias across multiple ice types. The accuracy of the method is verified through photogrammetric measurements, demonstrating that the derived DEM has a root-mean-square error of 0.26 m over a 200 km × 19 km area. The method is further applied to broader regions in the Weddell Sea and the Ross Sea, offering new insights into the regional variations of the sea ice topography in the Antarctic. We also characterize the non-Gaussian statistical behavior of the total freeboard using log-normal and exponential-normal distributions. The results suggest that the exponential-normal distribution is superior in the thicker-sea-ice region (average total freeboard > 0.5 m), whereas the two distributions exhibit similar performance in the thinner-ice region (average total freeboard < 0.5 m). These findings offer an in-depth representation of the total freeboard and roughness in the Weddell and Ross seas. The novel methodology introduced here can be conducted on time series data to comprehend the dynamics of the sea ice, including its growth and deformation.

The rapid changes occurring in the polar regions require an improved understanding of the processes that are driving these changes. At the same time, increased human activities such as marine navigation, resource exploitation, aviation, commercial fishing, and tourism require reliable and relevant weather information. One of the primary goals of the World Meteorological Organization's Year of Polar Prediction (YOPP) project is to improve the accuracy of numerical weather prediction (NWP) at high latitudes. During YOPP, two Canadian “supersites” were commissioned and equipped with new ground-based instruments for enhanced meteorological and system process observations. Additional pre-existing supersites in Canada, the United States, Norway, Finland, and Russia also provided data from ongoing long-term observing programs. These supersites collected a wealth of observations that are well suited to address YOPP objectives. In order to increase data useability and station interoperability, novel Merged Observatory Data Files (MODFs) were created for the seven supersites over two Special Observing Periods (February to March 2018 and July to September 2018). All observations collected at the supersites were compiled into this standardized NetCDF MODF format, simplifying the process of conducting pan-Arctic NWP verification and process evaluation studies. This paper describes the seven Arctic YOPP supersites, their instrumentation, data collection and processing methods, the novel MODF format, and examples of the observations contained therein. MODFs comprise the observational contribution to the model intercomparison effort, termed YOPP site Model Intercomparison Project (YOPPsiteMIP). All YOPPsiteMIP MODFs are publicly accessible via the YOPP Data Portal (Whitehorse: https://doi.org/10.21343/a33e-j150, Huang et al., 2023a; Iqaluit: https://doi.org/10.21343/yrnf-ck57, Huang et al., 2023b; Sodankylä: https://doi.org/10.21343/m16p-pq17, O'Connor, 2023; Utqiaġvik: https://doi.org/10.21343/a2dx-nq55, Akish and Morris, 2023c; Tiksi: https://doi.org/10.21343/5bwn-w881, Akish and Morris, 2023b; Ny-Ålesund: https://doi.org/10.21343/y89m-6393, Holt, 2023; and Eureka: https://doi.org/10.21343/r85j-tc61, Akish and Morris, 2023a), which is hosted by MET Norway, with corresponding output from NWP models.

Permafrost-affected ecosystems of the Arctic–boreal zone in northwestern North America are undergoing profound transformation due to rapid climate change. NASA's Arctic Boreal Vulnerability Experiment (ABoVE) is investigating characteristics that make these ecosystems vulnerable or resilient to this change. ABoVE employs airborne synthetic aperture radar (SAR) as a powerful tool to characterize tundra, taiga, peatlands, and fens. Here, we present an annotated guide to the L-band and P-band airborne SAR data acquired during the 2017, 2018, 2019, and 2022 ABoVE airborne campaigns. We summarize the ∼80 SAR flight lines and how they fit into the ABoVE experimental design (Miller et al., 2023; https://doi.org/10.3334/ORNLDAAC/2150). The Supplement provides hyperlinks to extensive maps, tables, and every flight plan as well as individual flight lines. We illustrate the interdisciplinary nature of airborne SAR data with examples of preliminary results from ABoVE studies including boreal forest canopy structure from TomoSAR data over Delta Junction, AK, and the Boreal Ecosystem Research and Monitoring Sites (BERMS) area in northern Saskatchewan and active layer thickness and soil moisture data product validation. This paper is presented as a guide to enable interested readers to fully explore the ABoVE L- and P-band airborne SAR data (https://uavsar.jpl.nasa.gov/cgi-bin/data.pl).

TP53 has been shown to be involved in lactation in cattle. However, the role of TP53 in buffalo lactation remains unknown. To this end, we isolated and identified the complete coding sequence (CDS) of the TP53 gene from the buffalo mammary gland and further analyzed its molecular characteristics, function, tissue differential expression, and single-nucleotide polymorphism (SNP). A transcript of this gene was cloned with a CDS length of 1161 bp, encoding a protein consisting of 386 amino acid residues. Bioinformatics analysis showed that buffalo TP53 CDS and the physicochemical characteristics, conserved domains, structure, and function of its encoded protein are highly similar to those of other species in Bovidae. The buffalo TP53 protein contains an N-terminal activation domain, a DNA-binding domain, and a tetrameric domain, and it plays a functional role in the nucleus. TP53 was found to express in all 11 detected buffalo tissues, and its expression in the heart, kidney, brain, muscle, and rumen during lactation was significantly higher than that during non-lactation (p), while in the liver, lung, and mammary gland, its expression was the opposite (p). Interference experiments in buffalo mammary epithelial cells (BuMECs) showed that TP53 inhibits the expression of genes related to milk protein and milk fat synthesis through the PI3K–AKT–mTOR pathway. A synonymous nucleotide substitution (c.204C > T) was found in the TP53 CDS of river buffalo, which is the CC homozygote in swamp buffalo. The results indicate that the TP53 gene is involved in buffalo lactation by negatively regulating the synthesis of milk protein and milk fat.

Investigating the global time-varying gravity field mainly depends on GRACE/GRACE-FO gravity data. However, satellite gravity data exhibit low spatial resolution and signal distortion. Satellite altimetry is an important technique for observing the global ocean and provides many consecutive years of data, which enables the study of high-resolution marine gravity variations. This study aims to construct a high-resolution marine gravity change rate (MGCR) model using multi-satellite altimetry data. Initially, multi-satellite altimetry data and ocean temperature–salinity data from 1993 to 2019 are utilized to estimate the altimetry sea level change rate (SLCR) and steric SLCR, respectively. Subsequently, the mass-term SLCR is calculated. Finally, based on the mass-term SLCR, the global MGCR model on 5′ × 5′ grids (SDUST2020MGCR) is constructed by applying the spherical harmonic function method and mass load theory. Comparisons and analyses are conducted between SDUST2020MGCR and GRACE2020MGCR resolved from GRACE/GRACE-FO gravity data. The spatial distribution characteristics of SDUST2020MGCR and GRACE2020MGCR are similar in the sea areas where gravity changes significantly, such as the eastern seas of Japan, the western seas of the Nicobar Islands, and the southern seas of Greenland. The statistical mean values of SDUST2020MGCR and GRACE2020MGCR in global and local oceans are all positive, indicating that MGCR is rising. Nonetheless, differences in spatial distribution and statistical results exist between SDUST2020MGCR and GRACE2020MGCR, primarily attributable to spatial resolution disparities among altimetry data, ocean temperature–salinity data, and GRACE/GRACE-FO data. Compared with GRACE2020MGCR, SDUST2020MGCR has higher spatial resolution and excludes stripe noise and leakage errors. The high-resolution MGCR model constructed using altimetry data can reflect the long-term marine gravity change in more detail, which is helpful in studying seawater mass migration and its associated geophysical processes. The SDUST2020MGCR model data are available at https://doi.org/10.5281/zenodo.10701641 (Zhu et al., 2024).

Various ground-based observing techniques provide precipitable water vapor (PWV) products with different spatial resolutions. To effectively integrate these products, especially in terms of vertical orientation, spatial interpolation is essential. In this context, we have developed a model to characterize PWV variation with altitude over our study area. Our model, known as RF-PWV (a PWV vertical correction grid model with a 1° × 1° resolution), is constructed using random forest based on the relationship between the differences in different pressure level PWV data from the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis (ERA5) monthly average hourly data and corresponding differences in their height differences over time. When validated against 1 h ERA5 PWV profiles, RF-PWV exhibits a 99.84 % reduction in bias and a 63.41 % decrease in the RMSE compared with the most recent model, C-PWVC1. Furthermore, when validated against radiosonde data, RF-PWV shows a 96.36 % reduction in bias and a 5 % decrease in the RMSE compared with C-PWVC1. Additionally, RF-PWV outperforms C-PWVC1 in terms of resistance to seasonal and height difference interference. The model eliminates the need for meteorological parameters, allowing for high-precision PWV vertical correction by inputting only time and height differences. Consequently, RF-PWV can significantly reduce errors in vertical correction, enhance PWV fusion product accuracy, and provide insights into PWV vertical distribution, thereby contributing to climate research.

Predicting future climate change over a region of complex terrain, such as the western United States (US), remains challenging due to the low resolution of global climate models (GCMs). Yet the climate extremes of recent years in this region, such as floods, wildfires, and drought, are likely to intensify further as climate warms, underscoring the need for high-quality and high-resolution predictions. Here, we present an ensemble of dynamically downscaled simulations over the western US from 1980–2100 at 9 km grid spacing, driven by 16 latest-generation GCMs. This dataset is titled the Western US Dynamically Downscaled Dataset (WUS-D3). We describe the challenges of producing WUS-D3, including GCM selection and technical issues, and we evaluate the simulations' realism by comparing historical results to temperature and precipitation observations. The future downscaled climate change signals are shaped in physically credible ways by the regional model's more realistic coastlines and topography. (1) The mean warming signals are heavily influenced by more realistic snowpack. (2) Mean precipitation changes are often consistent with wetting on the windward side of mountain complexes, as warmer, moister air masses are uplifted orographically during precipitation events. (3) There are large fractional precipitation increases on the lee side of mountain complexes, leading to potentially significant changes in water resources and ecology in these arid landscapes. (4) Increases in precipitation extremes are generally larger than in the GCMs, driven by locally intensified atmospheric updrafts tied to sharper, more realistic gradients in topography. (5) Changes in temperature extremes are different from what is expected by a shift in mean temperature and are shaped by local atmospheric dynamics and land surface feedbacks. Because of its high resolution, comprehensiveness, and representation of relevant physical processes, this dataset presents a unique opportunity to evaluate societally relevant future changes in western US climate.

Low rare earth content and high intrinsic magnetic properties make SmFe12-based permanent magnets a potential candidate for NdFeB-based magnets in medium to high temperature environments. However, the easy formation of multiple ferromagnetic intergranular phases limits the preparation of high coercivity magnets. Composition optimization is an indispensable measure for the realization of high-performance magnets. In this work, off-stoichiometric composition design is employed to prepare SmFe12-based alloys. Ti is first introduced to inhibit the precipitation of α-Fe phase, obtaining a high coercivity of 484 kA/m, while the ribbon undergoes a reduction of remanence significantly. After regulating Fe–Co content to 11.5, the remanence recoveries from 0.51 to 0.65 T with a slight increase in coercivity (484–493 kA/m). Finally, Fe content is optimized to further improve magnetic properties, with both coercivity and remanence are improved simultaneously, reaching 509 kA/m and 0.70 T, respectively. Phase evolution, microstructure and their relationship with magnetic properties are investigated in detail. Micromagnetic simulation shows that the increased domain wall pinning effect induced by the refinement of grain size is the main reason for high coercivity. This work provides a feasible compositional design method for the preparation of high performance SmFe12-based alloys.

Abstract Global climate models (GCMs) are unable to produce detailed runoff conditions at the basin scale. Assumptions are commonly made that dynamical downscaling can resolve this issue. However, given the large magnitude of the biases in downscaled GCMs, it is unclear whether such projections are credible. Here, we use an ensemble of dynamically downscaled GCMs to evaluate this question in the Sierra‐Cascade mountain range of the western US. Future projections across this region are characterized by earlier seasonal shifts in peak flow, but with substantial inter‐model uncertainty (−25 ± 34.75 days, 95% confidence interval (CI)). We apply the emergent constraint (EC) method for the first time to dynamically downscaled projections, leading to a 39% (−28.25 ± 20.75 days, 95% CI) uncertainty reduction in future peak flow timing. While the constrained results can differ from bias corrected projections, the EC is based on GCM biases in historical peak flow timing and has a strong physical underpinning.

Volatile organic compounds (VOCs) play a crucial role in the formation of tropospheric ozone (O3) and secondary organic aerosols. VOC emissions are generally considered to have larger uncertainties compared to other pollutants, such as sulfur dioxide and fine particulate matter (PM2.5). Although predictions of O3 and PM2.5 have been extensively evaluated in air quality modeling studies, there has been limited reporting on the evaluation of VOCs, mainly due to a lack of routine VOC measurements at multiple sites. In this study, we utilized VOC measurements from the “Towards an Air Toxic Management System in China” (ATMSYC) project at 28 sites across China and assessed the predicted VOC concentrations using the Community Multiscale Air Quality (CMAQ) model with the widely used Multi-resolution Emission Inventory for China (MEIC). The ratio of predicted to observed total VOCs was found to be 0.74 ± 0.40, with underpredictions ranging from 2.05 to 50.61 ppbv (5.77 % to 85.40 %) at 24 sites. A greater bias in VOC predictions was observed in industrial cities in the north and southwest, such as Jinan, Shijiazhuang, Lanzhou, Chengdu, and Guiyang. In terms of different VOC components, alkanes, alkenes, non-naphthalene aromatics (ARO2MN), alkynes, and formaldehyde (HCHO) had prediction-to-observation ratios of 0.53 ± 0.38, 0.51 ± 0.48, 0.31 ± 0.38, 0.41 ± 0.47, and 1.21 ± 1.61, respectively. Sensitivity experiments were conducted to assess the impact of the VOC prediction bias on O3 predictions. While emission adjustments improved the model performance for VOCs, resulting in a change in the ratio of total VOCs to 0.86 ± 0.47, they also exacerbated O3 overprediction relative to the base case by 0.62 % to 6.27 % across the sites. This study demonstrates that current modeling setups and emission inventories are likely to underpredict VOC concentrations, and this underprediction of VOCs contributes to lower O3 predictions in China.

A rope-climbing robot (RCR) can reciprocate on a rope. To address the problems of poor load capacity and adaptability of the existing RCR, this study designs a dual-rope crawler type RCR, which can be used as a new type of transportation equipment in hilly, mountainous, and plateau areas. The crawler rope-climbing mechanism is a combination of a chain drive and the rope-climbing foot. Innovatively applying the parabolic theory of overhead rope to kinematically analyze the rope-climbing robot system, the robot motion trajectory model and the tilt angle equation are established. To establish the safe working interval of the rope-climbing robot, the influence of machine load and rope span on robot tilt angle is compared. Furthermore, research on the dynamic characteristics of the rope-climbing robot is carried out, establishing a time-varying system model of the dynamic tension of the rope in the rope-climbing robot system and analyzing the effects of speed and load on the dynamic tension of the rope and system stability. Finally, the prototype test results show that the RCR operates stably and has good load capacity and barrier-crossing capability.

Atmospheric methane (CH4) concentrations have more than doubled since the beginning of the industrial age, making CH4 the second most important anthropogenic greenhouse gas after carbon dioxide (CO2). The oil and gas sector represents one of the major anthropogenic CH4 emitters as it is estimated to account for 22 % of global anthropogenic CH4 emissions. An airborne field campaign was conducted in April–May 2019 to study CH4 emissions from offshore gas facilities in the southern North Sea with the aim of deriving emission estimates using a top-down (measurement-led) approach. We present CH4 fluxes for six UK and five Dutch offshore platforms or platform complexes using the well-established mass balance flux method. We identify specific gas production emissions and emission processes (venting and fugitive or flaring and combustion) using observations of co-emitted ethane (C2H6) and CO2. We compare our top-down estimated fluxes with a ship-based top-down study in the Dutch sector and with bottom-up estimates from a globally gridded annual inventory, UK national annual point-source inventories, and operator-based reporting for individual Dutch facilities. In this study, we find that all the inventories, except for the operator-based facility-level reporting, underestimate measured emissions, with the largest discrepancy observed with the globally gridded inventory. Individual facility reporting, as available for Dutch sites for the specific survey date, shows better agreement with our measurement-based estimates. For all the sampled Dutch installations together, we find that our estimated flux of (122.9 ± 36.8) kg h−1 deviates by a factor of 0.64 (0.33–12) from reported values (192.8 kg h−1). Comparisons with aircraft observations in two other offshore regions (the Norwegian Sea and the Gulf of Mexico) show that measured, absolute facility-level emission rates agree with the general distribution found in other offshore basins despite different production types (oil, gas) and gas production rates, which vary by 2 orders of magnitude. Therefore, mitigation is warranted equally across geographies.

Modern pollen datasets are essential for pollen-based quantitative paleoclimate (e.g. precipitation) reconstructions, which can aid in better understanding recent climate change and its underlying forcing mechanisms. A modern pollen dataset based on surface sediments from 90 lakes in the shrub, meadow, steppe and desert regions of the central and western Tibetan Plateau (TP) was established to fill geographical gaps left by previous datasets. Ordination analyses of pollen data and climatic parameters revealed that annual precipitation is the dominant factor in modern pollen distribution on the central and western TP. A regional transfer function for annual precipitation was developed with weighted averaging partial least squares (WA-PLS), which suggests a good inference power of the modern pollen dataset for annual precipitation. A case study in which the transfer function was effectively applied to a fossil pollen record from Tangra Yumco on the central TP for paleoprecipitation reconstruction demonstrated the significance of the modern pollen dataset in a lower data region for paleoclimate change studies. Data from this study, including pollen data for each sample and information on the sampled sites (location, altitude and climate data), are openly available via the Zenodo portal (https://doi.org/10.5281/zenodo.8008474, Ma et al., 2023).

This paper studies the evolution and fluid distribution characteristics of a high-speed projectile’s cavity in the water based on joint research, a method involving experiment and numerical simulation. Specifically, we develop an experimental platform and a numerical calculation model for a high-speed projectile to observe its initial cavity evolution characteristics in the water at different velocities and close ranges. Additionally, this work investigates the evolution mechanism of the cavitation process and its fluid distribution law inside the cavity and studies the evolution characteristics of the cavitation stage under different velocities. The results reveal that after the projectile enters the water, the cavity is gourd-shaped and symmetrical, with a necking phenomenon at the tail and the cavity falling off. The cavitation process can be divided into the surface closure, saturation, deep closure, and collapse stages according to the fluid distribution changes in the cavity. Suppose the projectile has a certain speed with the water, its velocity increases. In that case, the cavity generation rate decreases, the growth rate of the water vapor volume in the cavity decreases, the peak water vapor volume content reduces, and the volume of air in the saturation phase of the cavity becomes increases having a range of 6% to 9%. Additionally, the cavity surface closure dimensionless time grows logarithmically as the velocity changes from 0 m/s to 500 m/s, the cavity saturation dimensionless time decreases approximately linearly, and the cavity depth closure dimensionless time is unaffected by velocity changes.

Glaciers are crucial sources of freshwater in particular for the arid lowlands surrounding High Mountain Asia. To better constrain glacio-hydrological models, annual, or even better, seasonal information about glacier mass changes is highly beneficial. In this study, we evaluate the suitability of very-high-resolution Pléiades digital elevation models (DEMs) to measure glacier mass balance at annual and seasonal scales in two regions of High Mountain Asia (Muztagh Ata in Eastern Pamirs and parts of western Nyainqêntanglha, south-central Tibetan Plateau), where recent estimates have shown contrasting glacier behaviour. The average annual mass balance in Muztagh Ata between 2019 and 2022 was −0.07 ± 0.20 m w.e. a−1, suggesting the continuation of a recent phase of slight mass loss following a prolonged period of balanced mass budgets previously observed. The mean annual mass balance in western Nyainqêntanglha was highly negative for the same period (−0.60 ± 0.15 m w.e. a−1), suggesting increased mass loss rates compared to the approximately previous 5 decades. The 2022 winter (+0.13 ± 0.24 m w.e.) and summer (−0.35 ± 0.15 m w.e.) mass budgets in Muztagh Ata and western Nyainqêntanglha (−0.03 ± 0.27 m w.e. in winter; −0.63 ± 0.07 m w.e. in summer) suggest winter- and summer-accumulation-type regimes, respectively. We support our findings by implementing the Sentinel-1-based Glacier Index to identify the firn and wet-snow areas on glaciers and characterize the accumulation type. The good match between the geodetic and Glacier Index results supports the potential of very-high-resolution Pléiades data to monitor mass balance at short timescales and improves our understanding of glacier accumulation regimes across High Mountain Asia.

The accuracy of tropospheric delay correction heavily depends on the quality of the tropospheric model, and the zenith tropospheric delay (ZTD) is an important factor affecting the tropospheric delay. Therefore, it is essential to establish a precise ZTD empirical model. The existing ZTD models are constrained by a single fitting function, lack consideration for daily cycle variations, and rely solely on data with one resolution for modeling. To address these limitations, we proposed a global piecewise ZTD empirical grid (GGZTD-P) model. This model considers the daily cycle variation and latitude factor of ZTD, using the sliding window algorithm based on fifth-generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis data (ERA5). The ZTD data from 545 radiosonde stations and the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) atmospheric reanalysis data are used to validate the accuracy of the GGZTD-P model. The results indicate that the GGZTD-P model outperforms the global pressure and temperature 3 (GPT3) model, exhibiting 26 % and 53 % lower bias and rms, respectively, when using radiosonde stations as reference values. Furthermore, when evaluated using MERRA-2 atmospheric reanalysis data, the GGZTD-P model consistently exhibits superior performance across various latitude regions. It is expected that the application of this new model will provide improved services for high-precision global navigation satellite system (GNSS) positioning and GNSS meteorology.

Since 1999, Environment and Climate Change Canada (ECCC) has been coordinating a multi-laboratory comparison of measurements of long-lived greenhouse gases in whole air samples collected at the Global Atmosphere Watch (GAW) Alert Observatory located in the Canadian High Arctic (82∘28′ N, 62∘30′ W). In this paper, we evaluate the measurement agreement of atmospheric CO2, CH4, N2O, SF6, and stable isotopes of CO2 (δ13C, δ18O) between leading laboratories from seven independent international institutions. The measure of success is linked to target goals for network compatibility outlined by the World Meteorological Organization's (WMO) GAW greenhouse gas measurement community. Overall, based on ∼ 8000 discrete flask samples, we find that the co-located atmospheric CO2 and CH4 measurement records from Alert by CSIRO, MPI-BGC, SIO, UHEI-IUP, and ECCC versus NOAA (the designated reference laboratory) are generally consistent with the WMO compatibility goals of ± 0.1 ppm CO2 and ± 2 ppb CH4 over the 17-year period (1999–2016), although there are periods where differences exceed target levels and persist as systematic bias for months or years. Consistency with the WMO goals for N2O, SF6, and stable isotopes of CO2 (δ13C, δ18O) has not been demonstrated. Additional analysis of co-located comparison measurements between CSIRO and SIO versus NOAA or INSTAAR (for the isotopes of CO2) at other geographical sites suggests that the findings at Alert for CO2, CH4, N2O, and δ13C–CO2 could be extended across the CSIRO, SIO, and NOAA observing networks. The primary approach to estimate an overall measurement agreement level was carried out by pooling the differences of all individual laboratories versus the designated reference laboratory and determining the 95th percentile range of these data points. Using this approach over the entire data record, our best estimate of the measurement agreement range is −0.51 to +0.53 ppm for CO2, −0.09 ‰ to +0.07 ‰ for δ13C, −0.50 ‰ to +0.58 ‰ for δ18O, −4.86 to +6.16 ppb for CH4, −0.75 to +1.20 ppb for N2O, and −0.14 to +0.09 ppt for SF6. A secondary approach of using the average of 2 standard deviations of the means for all flask samples taken in each individual sampling episode provided similar results. These upper and lower limits represent our best estimate of the measurement agreement at the 95 % confidence level for these individual laboratories, providing more confidence for using these datasets in various scientific applications (e.g., long-term trend analysis).

Elevated ground-level ozone concentrations have emerged as a major environmental issue in China. Nitrogen oxide (NOx) is a key precursor to ozone formation. Although control strategies aimed at reducing NOx emissions from conventional combustion sources are widely recognized, soil NOx emissions (mainly as NO) due to microbial processes have received little attention. The impact of soil NO emissions on ground-level ozone concentration is yet to be evaluated. This study estimated soil NO emissions in China using the Berkeley–Dalhousie Soil NOx Parameterization (BDSNP) algorithm. A typical modeling approach was used to quantify the contribution of soil NO emissions to surface ozone concentration. The brute-force method (BFM) and the Ozone Source Apportionment Technology (OSAT) implemented in the Comprehensive Air Quality Model with Extensions (CAMx) were used. The total soil NO emissions in China for 2018 were estimated to be 1157.9 Gg N, with an uncertainty range of 715.7–1902.6 Gg N. Spatially, soil NO emissions are mainly concentrated in Central China, North China, Northeast China, the northern Yangtze River Delta (YRD), and the eastern Sichuan Basin, with distinct diurnal and monthly variations that are mainly affected by the temperature and timing of fertilizer application. Both the BFM and OSAT results indicate a substantial contribution of soil NO emissions to the maximum daily 8 h (MDA8) ozone concentrations by 8.0–12.5 µg m−3 on average for June 2018, with the OSAT results being consistently higher than the BFM results. The results also showed that soil NO emissions led to a relative increase in ozone exceedance days by 10.5 %–43.5 % for selected regions. Reducing the soil NO emissions resulted in a general decrease in monthly MDA8 ozone concentrations, and the magnitude of ozone reduction became more pronounced as reductions increased. However, even with complete reductions in soil NO emissions, approximately 450.3 million people are still exposed to unhealthy ozone levels, necessitating multiple control policies at the same time. This study highlights the importance of soil NO emissions for ground-level ozone concentrations and the potential for reducing NO emissions as a future control strategy for ozone mitigation in China.

Quantifying the full-volatility organic emissions from cooking sources is important for understanding the causes of organic aerosol pollution. However, existing national cooking emission inventories in China fail to cover full-volatility organics and have large biases in estimating emissions and their spatial distribution. Here, we develop the first emission inventory of full-volatility organics from cooking in China, which covers emissions from individual commercial restaurants as well as residential kitchens and canteens. In our emission estimates, we use cuisine-specific full-volatility emission factors and provincial policy-driven purification facility installation proportions, which allows us to consider the significant impact of diverse dietary preferences and policy changes on China's cooking emissions. The 2021 emissions of volatile organic compounds (VOCs), intermediate-volatility organic compounds (IVOCs), semi-volatile organic compounds (SVOCs), and organic compounds with even lower volatility (xLVOCs) from cooking in China are 561 (317–891, 95 % confidence interval) kt yr−1, 241 (135–374) kt yr−1, 176 (95.8–290) kt yr−1, and 13.1 (7.36–21.0) kt yr−1, respectively. The IVOC and SVOC emissions from cooking account for 9 %–21 % and 31 %–62 % of the total emissions from all sources in the five most densely populated cities in China. Among all cooking types, commercial cooking dominates the emissions, contributing 54.5 %, 66.2 %, 68.5 %, and 46.7 % to the VOC, IVOC, SVOC, and xLVOC emissions, respectively. Sichuan–Hunan cuisine contributes the most to total cooking emissions among all commercial cuisines. Residential cooking emissions are also important, accounting for 22.2 %–47.1 % of the cooking organic emissions across the four volatility ranges, whereas canteens make minor contributions to each volatility range (%). In terms of spatial distribution, emission hotspots mainly occur in densely populated areas and regions with oily and spicy dietary preferences. From 2015 to 2021, national organic emissions from cooking increased by 25.2 % because of the rapid growth of the catering industry, despite being partly offset by the increased installation of purification facilities. Future control measures need to further promote the purification facilities in commercial restaurants and improve their removal efficiency as well as reduce emissions from residential cooking. Our dataset and generalizable methodology serve as valuable resources for evaluating the air quality, climate, and health impacts of cooking sources, and help to formulate effective emission control policies. Our national, multi-year, high-spatial-resolution dataset can be accessed from https://doi.org/10.6084/m9.figshare.23537673 (Li et al., 2023).

Low-frequency buffeting is a common problem in automobile wind tunnels, it induces pulsations of pressure and velocity in the test section. A 1:15 3/4 open-jet return-type scaled wind tunnel was used for this research, and numerical simulations and tests were implemented to study the flow characteristics of the jet shear layer in a model wind tunnel. The results show that guide devices on the inner wall of the nozzle can effectively reduce the low-frequency buffeting, but the presence of the devices deteriorated the axial static pressure gradient of the flow in the test section. The shape of the guide devices was optimized through the Explorative Gradient Method, and numerical simulations were carried out. An optimal shape can effectively reduce the low-frequency buffeting and ensure flow field uniformity in the test section. Finally, the reliability of the numerical simulation and the practicability of the optimal case were verified through a hot wire test and a microphone test.

Molecular markers in organic aerosol (OA) provide specific source information on PM2.5, and the contribution of cooking organic aerosols to OA is significant, especially in urban environments. However, the low time resolution of offline measurements limits the effectiveness when interpreting the tracer data, the diurnal variation in cooking emissions and the oxidation process. In this study, we used online thermal desorption aerosol gas chromatography and mass spectrometry (TAG) to measure organic molecular markers in fine particulate matter (PM2.5) at an urban site in Changzhou, China. The concentrations of saturated fatty acids (sFAs), unsaturated fatty acids (uFAs) and oxidative decomposition products (ODPs) of unsaturated fatty acids were measured every 2 h to investigate the temporal variations and the oxidative decomposition characteristics of uFAs in urban environments. The average concentration of total fatty acids (TFAs, sum of sFAs and uFAs) was measured to be 105.70±230.28 ng m−3. The average concentration of TFAs in the polluted period (PM2.5≥35 µg m−3) was 147.06 ng m−3, which was 4.2 times higher than that in the clean period (PM2.5 µg m−3) and higher than the enhancement of PM2.5 (2.2 times) and organic carbon (OC) (2.0 times) concentrations when comparing the polluted period to the clean period. The mean concentration of cooking aerosol in the polluted period (4.0 µg m−3) was about 5.3 times higher than that in the clean period (0.75 µg m−3), which was similar to the trend of fatty acids. Fatty acids showed a clear diurnal variation. Linoleic acid / stearic acid and oleic acid / stearic acid ratios were significantly higher at dinnertime and closer to the cooking source profile. By performing backward trajectory clustering analysis, under the influence of short-distance air masses from surrounding areas, the concentrations of TFAs and PM2.5 were relatively high, while under the influence of air masses from easterly coastal areas, the oxidation degree of uFAs emitted from local culinary sources was higher. The effective rate constants (kO) for the oxidative degradation of oleic acid were estimated to be 0.08–0.57 h−1, which were lower than kL (the estimated effective rate constants of linoleic acid, 0.16–0.80 h−1). Both kO and kL showed a significant positive correlation with O3, indicating that O3 was the main nighttime oxidant for uFAs in the city of Changzhou. Using fatty acids as tracers, cooking was estimated to contribute an average of 4.6 % to PM2.5 concentrations, increasing to 7.8 % at 20:00 UTC+8 h. Cooking was an important source of OC, contributing 8.1 %, higher than the contribution of PM2.5. This study investigates the variation in the concentrations and oxidative degradation of fatty acids and corresponding oxidation products in ambient air, which can be a guide for the refinement of aerosol source apportionment and provide scientific support for the development of cooking source control policies.

Polychlorinated biphenyls (PCBs) are nowadays mainly unintentionally produced, since their use and manufacture has been banned. PCBs, especially those dioxin-like compounds, have been proven harmful to ecosystems and human health. Detailed information about the spatiotemporally distribution of unintentionally produced PCBs (UP-PCBs) is crucial for understanding the environmental fate and associated health risks. However, research estimating UP-PCBs emission in China is limited. In this study, a source-specific and year-varying emission factor (EF) dataset was used to compile provincial emissions of 12 dioxin-like UP-PCBs congeners for 66 sources in the Chinese mainland from 1960 to 2019. In addition to that, emissions for 2019 were allocated into 0.1∘×0.1∘ grids. The results indicated that historical national UP-PCBs emission represented an increasing trend until around 1995 and then showed an overall decreasing trend from 1995 to 2019. Cement production was the largest UP-PCBs emission source in the Chinese mainland. Geographically, East and North China contributed the largest UP-PCBs emission across the Chinese mainland. High emission densities occurred mainly in the densely populated and well-developed regions such as Yangtze River Delta Urban Agglomeration and Pearl River Delta. Furthermore, highly positive correlations of emission densities with population and GDP densities were identified.

The representation of aerosol–cloud interaction (ACI) and its impacts in the current climate or weather model remains a challenge, especially for severely polluted regions with high aerosol concentration, which is even more important and worthy of study. Here, ACI is first implemented in the atmospheric chemistry model GRAPES_Meso5.1/CUACE by allowing for real-time aerosol activation in the Thompson cloud microphysics scheme. Two experiments are conducted focusing on a haze pollution case with coexisting high aerosol and stratus cloud over the Jing–Jin–Ji region in China to investigate the impact of ACI on the mesoscale numerical weather prediction (NWP). Study results show that ACI increases cloud droplet number concentration, water mixing ratio, liquid water path (CLWP), and optical thickness (COT), as a result improving the underestimated CLWP and COT (reducing the mean bias by 21 % and 37 %, respectively) over a certain subarea by the model without ACI. A cooling in temperature in the daytime below 950 hPa occurs due to ACI, which can reduce the mean bias of 2 m temperature in the daytime by up to 14 % (∼ 0.6 ∘C) in the subarea with the greatest change in CLWP and COT. The 24 h cumulative precipitation in this subarea corresponding to moderate-rainfall events increases, which can reduce the mean bias by 18 %, depending on the enhanced melting of the snow by more cloud droplets. In other areas or periods with a slight change in CLWP and COT, the impact of ACI on NWP is not significant, suggesting the inhomogeneity of ACI. This study demonstrates the critical role of ACI in the current NWP model over the severely polluted region and the complexity of the ACI effect.

The changing Arctic climate is creating increased economic, transportation, and recreational activities requiring reliable and relevant weather information. However, the Canadian Arctic is sparsely observed, and processes governing weather systems in the Arctic are not well understood. There is a recognized lack of meteorological data to characterize the Arctic atmosphere for operational forecasting and to support process studies, satellite calibration/validation, search and rescue operations (which are increasing in the region), high-impact weather (HIW) detection and prediction, and numerical weather prediction (NWP) model verification and evaluation. To address this need, Environment and Climate Change Canada commissioned two supersites, one in Iqaluit (63.74∘ N, 68.51∘ W) in September 2015 and the other in Whitehorse (60.71∘ N, 135.07∘ W) in November 2017 as part of the Canadian Arctic Weather Science (CAWS) project. The primary goals of CAWS are to provide enhanced meteorological observations in the Canadian Arctic for HIW nowcasting (short-range forecast) and NWP model verification, evaluation, and process studies and to provide recommendations on the optimal cost-effective observing system for the Canadian Arctic. Both sites are in provincial/territorial capitals and are economic hubs for the region; they also act as transportation gateways to the north and are in the path of several common Arctic storm tracks. The supersites are located at or next to major airports and existing Meteorological Service of Canada ground-based weather stations that provide standard meteorological surface observations and upper-air radiosonde observations; they are also uniquely situated in close proximity to frequent overpasses by polar-orbiting satellites. The suite of in situ and remote sensing instruments at each site is completely automated (no on-site operator) and operates continuously in all weather conditions, providing near-real-time data to operational weather forecasters, the public, and researchers via obrs.ca. The two sites have similar instruments, including mobile Doppler weather radars, multiple vertically profiling and/or scanning lidars (Doppler, ceilometer, water vapour), optical disdrometers, precipitation gauges in different shielded configurations, present weather sensors, fog monitoring devices, radiation flux sensors, and other meteorological instruments. Details on the two supersites, the suites of instruments deployed, the data collection methods, and example case studies of HIW events are discussed. CAWS data are publicly accessible via the Canadian Government Open Data Portal (https://doi.org/10.18164/ff771396-b22c-4bc3-844d-38fc697049e9, Mariani et al., 2022a, and https://doi.org/10.18164/d92ed3cf-4ba0-4473-beec-357ec45b0e78, Mariani et al., 2022b); this dataset is being used to improve our understanding of synoptic and fine-scale meteorological processes in the Arctic and sub-Arctic, including HIW detection and prediction and NWP verification, assimilation, and processes.

Pedestrian dead reckoning (PDR) can solve the position information by its inertial measurement unit (IMU), which is a method to achieve indoor autonomous positioning without deploying positioning base stations in advance. However, affected by the accumulated error, the positioning accuracy will decrease with the increase of the moving distance. To improve the indoor positioning accuracy, the step length estimation of PDR is improved. A PDR method combining the information on walking frequency, acceleration variance, and fixed step is proposed. Firstly, the pedestrian's walking steps are detected and estimated by the threshold peak method; secondly, the step frequency and acceleration variance are calculated, and the step length estimation model is fitted with the fixed step length of the pedestrian to estimate the step length of each step; then, the fusion algorithm of magnetometer, accelerometer, and gyroscope are used to estimate the heading; finally, combined with the step number, step length, and heading angle, the position information of walking is calculated by dead reckoning. The experimental results show that in the practical distance of 42.6 m, the accuracy of dead reckoning distance based on the combination of step frequency, acceleration variance, and fixed step length can reach 98.47%, which is better than the fixed step length and linear step length version, 5.09% higher than the linear step length and 0.35% higher than the fixed step length version.

Nitrate (NO3−) has been the dominant and the least reduced chemical component of fine particulate matter (PM2.5) since the stringent emission controls implemented in China in 2013. The formation pathways of NO3− vary seasonally and differ substantially in daytime vs. nighttime. They are affected by precursor emissions, atmospheric oxidation capacity, and meteorological conditions. Understanding NO3− formation pathways provides insights for the design of effective emission control strategies to mitigate NO3− pollution. In this study, the Community Multiscale Air Quality (CMAQ) model was applied to investigate the impact of regional transport, predominant physical processes, and different formation pathways to NO3− and total nitrate (TNO3, i.e., HNO3+ NO3−) production in the Yangtze River Delta (YRD) region during the four seasons of 2017. NO3-/PM2.5 and NO3-/TNO3 are the highest in the winter, reaching 21 % and 94 %, respectively. The adjusted gas ratio (adjGR = ([NH3]+ [NO3−])/([HNO3]+ [NO3−])) in the YRD is generally greater than 2 in the four seasons across most areas in the YRD, indicating that YRD is mostly in the NH3-rich regime and that NO3− is limited by HNO3 formation. Local emissions and regional transportation contribute to NO3− concentrations throughout the YRD region by 50 %–62 % and 38 %–50 %, respectively. The majority of the regional transport of NO3− concentrations is contributed by indirect transport (i.e., NO3− formed by transported precursors reacting with local precursors). Aerosol (AERO, including condensation, coagulation, new particle formation, and aerosol growth) processes are the dominant source of NO3− formation. In summer, NO3− formation is dominated by AERO and total transport (TRAN, sum of horizontal and vertical transport) processes. The OH + NO2 pathway contributes to 60 %–83 % of the TNO3 production, and the N2O5 heterogeneous (HET N2O5) pathway contributes to 10 %–36 % in the YRD region. HET N2O5 contribution becomes more important in cold seasons than warm seasons. Within the planetary boundary layer in Shanghai, the TNO3 production is dominated by the OH + NO2 pathway during the day (98 %) in the summer and spring and by the HET N2O5 pathway during the night (61 %) in the winter. Local contributions dominate the OH + NO2 pathway for TNO3 production during the day, while indirect transport dominates the HET N2O5 pathway at night.

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.

In this paper, a novel high-sensitivity broadband rectifier is proposed aiming at ambient radio frequency (RF) energy harvesting. Traditionally, voltage doubling rectifying circuit is used to design high-sensitivity rectifier. But when the input power is lower, the rectifying efficiency is significantly reduced. Therefore, a improved parallel half-wave rectifying circuit is proposed in this article which can convert RF energy in the whole period. And the proposed rectifying circuit can work better in lower power environment and has a higher efficiency level. Besides, the impedance match is also important component of rectifier. Due to the nonlinearity and complexity of rectifying circuit, achieving wideband matching network is a challenge. Thus, a design approach of broadband impedance circuit is given in this study. Combining with the proposed high-sensitivity rectifying circuit, a high-sensitivity wideband rectifier can be generated, when the input power is -15dBm, -20dBm, -25dBm, the efficiency is 43%, 32%, 20%, respectively. Finally, a second-order wideband rectifier with high sensitivity is realized, and the range of bandwidth can cover four main frequency bands of GSM 900 MHz, GSM 1800 MHz, UMTS 2100 MHz, WLAN 2400 MHz. To verify the validity, the rectifier is fabricated and measured, and the measurement has a good agreement with simulation results.

We have carried out a detailed study of individual pulse emission from the pulsar J2022+5154 (B2021+51), observed at 2250 MHz using the Jiamusi 66 m radio telescope. We have investigated the modulations in single-pulse behavior using fluctuation spectral analysis, which shows the presence of two prominent periodicities, around 5 and 40 rotation periods, respectively. The shorter periodicity is associated with the phenomenon of subpulse drifting. In the absence of aliasing, the emission pattern is demonstrated to consist of eight subbeams, which rotate around the magnetic axis in about 45 periods. In addition to subpulse drifting, the pulsar also shows the presence of periodic amplitude modulation with a longer periodicity in the single-pulse sequence. The pulsar joins a select group that shows the presence of periodic phase-modulated drifting as well as amplitude-modulated drifting. This provides further evidence for the two phenomena being distinct from each other with different physical origins.

In this paper, an innovative cylindrical deployable mechanism (DM) based on rigid origami is presented, which is used to design a parabolic cylindrical deployable antenna. The mechanism can be deployed from the cuboid folded configuration to the cylindrical unfolded configuration with only one actuator. First, an innovative deployable string is proposed based on different types of four-vertices origami unit cells and kirigami techniques. By considering the units as 6R single-loop mechanisms, the kinematics of the origami unit cells are analyzed. Through the connection of identical deployable strings, the cylindrical DM is constructed, and its mobility is analyzed utilizing the screw theory. Then the proposed DM is used to design a parabolic cylindrical deployable antenna. A number of pillars are installed on the panels of the DM, and their lengths are determined to fit the required parabolic cylindrical surface. To verify the feasibility of the design, a scaled prototype of the deployable antenna is constructed.

The important Qinghai–Tibet Engineering Corridor (QTEC) covers the part of the Highway and Railway underlain by permafrost. The permafrost on the QTEC is sensitive to climate warming and human disturbance and suffers accelerating degradation. Retrogressive thaw slumps (RTSs) are slope failures due to the thawing of ice-rich permafrost. They typically retreat and expand at high rates, damaging infrastructure, and releasing carbon preserved in frozen ground. Along the critical and essential corridor, RTSs are commonly distributed but remain poorly investigated. To compile the first comprehensive inventory of RTSs, this study uses an iteratively semi-automatic method built on deep learning to delineate thaw slumps in the 2019 PlanetScope CubeSat images over a ∼ 54 000 km2 corridor area. The method effectively assesses every image pixel using DeepLabv3+ with limited training samples and manually inspects the deep-learning-identified thaw slumps based on their geomorphic features and temporal changes. The inventory includes 875 RTSs, of which 474 are clustered in the Beiluhe region, and 38 are near roads or railway lines. The dataset is available at https://doi.org/10.5281/zenodo.6397029​​​​​​​ (Xia et al., 2021a), with the Chinese version at DOI: https://doi.org/10.11888/Cryos.tpdc.272672 (Xia et al. 2021b). These RTSs tend to be located on north-facing slopes with gradients of 1.2–18.1∘ and distributed at medium elevations ranging from 4511 to 5212 m a.s.l. They prefer to develop on land receiving relatively low annual solar radiation (from 2900 to 3200 kWh m−2), alpine meadow covered, and loam underlay. Our results provide a significant and fundamental benchmark dataset for quantifying thaw slump changes in this vulnerable region undergoing strong climatic warming and extensive human activities.

To reveal the regulation mechanism of terpenoid biosynthesis in the leaves of Eucalyptus camaldulensis, the content of volatiles in eucalyptus leaves and the transcriptome databases of young and mature leaves were analyzed. The results showed that E. camaldulensis contains 92 and 89 kinds of volatile substances in the young and mature leaves, respectively. Among them, the content of 1,8-cineole, β-pinene, and other substances was significantly different in young and mature leaves. A total of 99 802 unigenes were obtained from the transcriptome database of young and mature leaves of E. camaldulensis and 18 441 genes displayed obviously differential expressions during both developmental stages. There were 6 982 up-regulated unigenes and 11 461 down-regulated unigenes in the young leaf stage compared to the mature leaf stage. The key genes for terpenoid biosynthesis, including limonene synthase-10, limonene synthase-11, myrcene synthase-1, α- pinene synthase-2, and 1,8-cineole synthase-2, were selected for further analysis to explore the mechanism of gene regulation and genetic transformation. The expressions of key genes were validated by RT-qPCR, and their expressions were consistent with RNA-seq data. WRKY, MYB, NAC, and bHLH transcription factors (TFs) displayed important regulatory effects on the above key genes. Thus, a regulatory network model of terpenoid biosynthesis was constructed using target genes and TFs during leaf development in E. camaldulensis. These results provide theoretical evidence for understanding the terpenoid biosynthesis in plants and reference for terpenoids utilization by genetic engineering methods in E. camaldulensis.

While carbon dioxide is the main cause for global warming, modeling short-lived climate forcers (SLCFs) such as methane, ozone, and particles in the Arctic allows us to simulate near-term climate and health impacts for a sensitive, pristine region that is warming at 3 times the global rate. Atmospheric modeling is critical for understanding the long-range transport of pollutants to the Arctic, as well as the abundance and distribution of SLCFs throughout the Arctic atmosphere. Modeling is also used as a tool to determine SLCF impacts on climate and health in the present and in future emissions scenarios. In this study, we evaluate 18 state-of-the-art atmospheric and Earth system models by assessing their representation of Arctic and Northern Hemisphere atmospheric SLCF distributions, considering a wide range of different chemical species (methane, tropospheric ozone and its precursors, black carbon, sulfate, organic aerosol, and particulate matter) and multiple observational datasets. Model simulations over 4 years (2008–2009 and 2014–2015) conducted for the 2022 Arctic Monitoring and Assessment Programme (AMAP) SLCF assessment report are thoroughly evaluated against satellite, ground, ship, and aircraft-based observations. The annual means, seasonal cycles, and 3-D distributions of SLCFs were evaluated using several metrics, such as absolute and percent model biases and correlation coefficients. The results show a large range in model performance, with no one particular model or model type performing well for all regions and all SLCF species. The multi-model mean (mmm) was able to represent the general features of SLCFs in the Arctic and had the best overall performance. For the SLCFs with the greatest radiative impact (CH4, O3, BC, and SO42-), the mmm was within ±25 % of the measurements across the Northern Hemisphere. Therefore, we recommend a multi-model ensemble be used for simulating climate and health impacts of SLCFs. Of the SLCFs in our study, model biases were smallest for CH4 and greatest for OA. For most SLCFs, model biases skewed from positive to negative with increasing latitude. Our analysis suggests that vertical mixing, long-range transport, deposition, and wildfires remain highly uncertain processes. These processes need better representation within atmospheric models to improve their simulation of SLCFs in the Arctic environment. As model development proceeds in these areas, we highly recommend that the vertical and 3-D distribution of SLCFs be evaluated, as that information is critical to improving the uncertain processes in models.

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.

In recent years, audio positioning technology has been more favoured because it is not only highly accurate but also universally applicable to the mass users. In line with this trend, a chip dedicated to indoor positioning, the Kepler A100, has been released lately, which ranges by estimating the arrival time of the audio chirp. As with radio ranging techniques, sound-based ranging methods is subject to significant observation errors due to Non-Line-Of-Sight (NLOS) or multi-path effects, while Pedestrian Dead Reckoning (PDR) based on inertial data have the disadvantage of error accumulation. Both make localization challenging. In this paper, the ranging performance of the Kepler A100 chip is evaluated and experiments are conducted in two typical indoor scenarios to verify the stability and sub-metre accuracy of the ranging results. Meanwhile, this paper implements an indoor positioning system combining audio chirp/Micro-Electro-Mechanical Systems (MEMS)/floor map based on particle filtering algorithm. A new mapping constraint method is applied in the system, which can effectively constrain the particles in a reasonable space. Experiments are conducted in two complex office environments and the results show that the error of the proposed algorithm is about 0.65m in 95% of cases, a reduction of more than 40% compared to only-PDR or only-audio. The effectiveness and stability of the method is demonstrated.

The outbreak of COVID-19 promoted strict restrictions to human activities in China, which led to a dramatic decrease in most air pollutant concentrations (e.g., PM2.5, PM10, NOx, SO2 and CO). However, an obvious increase in ozone (O3) concentrations was found during the lockdown period in most urban areas of China. In this study, we conducted field measurements targeting ozone and its key precursors by utilizing a novel proton transfer reaction time-of-flight mass spectrometer (PTR-TOF-MS) in Changzhou, which is representative of the Yangtze River Delta (YRD) city cluster of China. We further applied the integrated methodology including machine learning, an observation-based model (OBM) and sensitivity analysis to obtain insights into the reasons causing the obvious increase in ozone. Major findings include the following: (1) by deweathered calculation, we found changes in precursor emissions contributed 1.46 ppbv to the increase in the observed O3 during the full-lockdown period in 2020, while meteorology constrained 3.0 ppbv of O3 in the full-lockdown period of 2019. (2) By using an OBM, we found that although a significant reduction in O3 precursors was observed during the full-lockdown period, the photochemical formation of O3 was stronger than that during the pre-lockdown period. (3) The NOx/VOC ratio dropped dramatically from 1.84 during the pre-lockdown to 0.79 in the full-lockdown period, which switched O3 formation from a VOC-limited regime to the boundary of a NOx- and VOC-limited regime. Additionally, box model results suggested that the decrease in the NOx/VOC ratio during the full-lockdown period could increase the mean O3 by 2.4 ppbv. Results of this study give insights into the relationship between O3 and its precursors in urban area and demonstrate reasons for the obvious increase in O3 in most urban areas of China during the COVID-19 lockdown period. This study also underlines the necessity of controlling anthropogenic oxygenated volatile organic compounds (OVOCs), alkenes and aromatics in the sustained campaign of reducing O3 pollution in China.

The oil and gas (O&G) sector is a significant source of methane (CH4) emissions. Quantifying these emissions remains challenging, with many studies highlighting discrepancies between measurements and inventory-based estimates. In this study, we present CH4 emission fluxes from 21 offshore O&G facilities collected in 10 O&G fields over two regions of the Norwegian continental shelf in 2019. Emissions of CH4 derived from measurements during 13 aircraft surveys were found to range from 2.6 to 1200 t yr−1 (with a mean of 211 t yr−1 across all 21 facilities). Comparing this with aggregated operator-reported facility emissions for 2019, we found excellent agreement (within 1σ uncertainty), with mean aircraft-measured fluxes only 16 % lower than those reported by operators. We also compared aircraft-derived fluxes with facility fluxes extracted from a global gridded fossil fuel CH4 emission inventory compiled for 2016. We found that the measured emissions were 42 % larger than the inventory for the area covered by this study, for the 21 facilities surveyed (in aggregate). We interpret this large discrepancy not to reflect a systematic error in the operator-reported emissions, which agree with measurements, but rather the representativity of the global inventory due to the methodology used to construct it and the fact that the inventory was compiled for 2016 (and thus not representative of emissions in 2019). This highlights the need for timely and up-to-date inventories for use in research and policy. The variable nature of CH4 emissions from individual facilities requires knowledge of facility operational status during measurements for data to be useful in prioritising targeted emission mitigation solutions. Future surveys of individual facilities would benefit from knowledge of facility operational status over time. Field-specific aggregated emissions (and uncertainty statistics), as presented here for the Norwegian Sea, can be meaningfully estimated from intensive aircraft surveys. However, field-specific estimates cannot be reliably extrapolated to other production fields without their own tailored surveys, which would need to capture a range of facility designs, oil and gas production volumes, and facility ages. For year-on-year comparison to annually updated inventories and regulatory emission reporting, analogous annual surveys would be needed for meaningful top-down validation. In summary, this study demonstrates the importance and accuracy of detailed, facility-level emission accounting and reporting by operators and the use of airborne measurement approaches to validate bottom-up accounting.

This empirical research aims to propose and examine an online teaching approach that embeds modeling-eliciting activities (MEA). The approach guides teachers to create a well-interactive online learning environment and improve the conceptual learning and professional skills of engineering undergraduates. The professional skills are defined as critical thinking and collaboration. A structured teaching procedure was implemented sequentially by task introduction, problem description, performance analysis, structural optimization, and solution discussion. The six principles of MEA were organically integrated with the teaching procedure, creating a inspiring, open-ended, and teamwork learning environment. The instruments used to collect data included conceptual learning tests, design report evaluations, learning reflection analyses, and interaction statistics. The findings suggested that the MEA-embedded online courses have significant advantages for improving learners’ conceptual learning and professional skills. The proposed approach guides the learners to make appropriate decisions and practical actions, enhancing their critical thinking. The MEA inspires learners’ positive attitudes and high participation, providing an emotional basis for group collaboration. The discussions on the open topics and thought process reflections create a collaborative environment. Besides, the statistics on the online teaching platform show that the MEA has a significant role for interaction promotion in the online course.

Single-pass interferometric synthetic aperture radar (InSAR) enables the possibility for sea ice topographic retrieval despite the inherent dynamics of sea ice. InSAR digital elevation models (DEMs) are measuring the radar scattering center height. The height bias induced by the penetration of electromagnetic waves into snow and ice leads to inaccuracies of the InSAR DEM, especially for thick and deformed sea ice with snow cover. In this study, an elevation difference between the satellite-measured InSAR DEM and the airborne-measured optical DEM is observed from a coordinated campaign over the western Weddell Sea in Antarctica. The objective is to correct the penetration bias and generate a precise sea ice topographic map from the single-pass InSAR data. With the potential of retrieving sea ice geophysical information by the polarimetric-interferometry (Pol-InSAR) technique, a two-layer-plus-volume model is proposed to represent the sea ice vertical structure and its scattering mechanisms. Furthermore, a simplified version of the model is derived, to allow its inversion with limited a priori knowledge, which is then applied to a topographic retrieval scheme. The experiments are performed across four polarizations: HH, VV, Pauli 1 (HH + VV), and Pauli 2 (HH − VV). The model-retrieved performance is validated with the optically derived DEM of the sea ice topography, showing an excellent performance with root-mean-square error as low as 0.26 m in Pauli-1 (HH + VV) polarization.

While climate change mitigation targets necessarily concern maximum mean state changes, understanding impacts and developing adaptation strategies will be largely contingent on how climate variability responds to increasing anthropogenic perturbations. Thus far Earth system modeling efforts have primarily focused on projected mean state changes and the sensitivity of specific modes of climate variability, such as the El Niño–Southern Oscillation. However, our knowledge of forced changes in the overall spectrum of climate variability and higher-order statistics is relatively limited. Here we present a new 100-member large ensemble of climate change projections conducted with the Community Earth System Model version 2 over 1850–2100 to examine the sensitivity of internal climate fluctuations to greenhouse warming. Our unprecedented simulations reveal that changes in variability, considered broadly in terms of probability distribution, amplitude, frequency, phasing, and patterns, are ubiquitous and span a wide range of physical and ecosystem variables across many spatial and temporal scales. Greenhouse warming in the model alters variance spectra of Earth system variables that are characterized by non-Gaussian probability distributions, such as rainfall, primary production, or fire occurrence. Our modeling results have important implications for climate adaptation efforts, resource management, seasonal predictions, and assessing potential stressors for terrestrial and marine ecosystems.

Dentin bonding is a dynamic process that involves the penetration of adhesive resin monomers into the extrafibrillar and intrafibrillar demineralized collagen matrix using a wet-bonding technique. However, adhesive resin monomers lack the capacity to infiltrate the intrafibrillar space, and the excess water that is introduced by the wet-bonding technique remains at the bonding interface. This imperfectly bonded interface is inclined to hydrolytic degradation, severely jeopardizing the longevity of bonded clinical restorations. The present study introduces a dentin bonding scheme based on a dry-bonding technique, combined with the use of extrafibrillar demineralization and a collagen-reactive monomer (CRM)-based adhesive (CBA). Selective extrafibrillar demineralization was achieved using 1-wt% high-molecular weight (MW) carboxymethyl chitosan (CMCS) within a clinically acceptable timeframe to create a less aggressive bonding substance for dentin bonding due to its selectively extrafibrillar demineralization capacity. CMCS demineralization decreased the activation of in situ collagenase, improved the shrinking resistance of demineralized collagen, and thus provided stronger and more durable bonding than traditional phosphoric acid etching. The new dentin bonding scheme that contained CMCS and CBA and used a dry-bonding technique achieved an encouraging dentin bonding strength and durability with low technical sensitivity. This bonding scheme can be used to improve the stability of the resin-dentin interface and foster the longevity of bonded clinical restorations.

In recent years, the pan-Arctic region has experienced increasingly extreme fire seasons. Fires in the northern high latitudes are driven by current and future climate change, lightning, fuel conditions, and human activity. In this context, conceptualizing and parameterizing current and future Arctic fire regimes will be important for fire and land management as well as understanding current and predicting future fire emissions. The objectives of this review were driven by policy questions identified by the Arctic Monitoring and Assessment Programme (AMAP) Working Group and posed to its Expert Group on Short-Lived Climate Forcers. This review synthesizes current understanding of the changing Arctic and boreal fire regimes, particularly as fire activity and its response to future climate change in the pan-Arctic have consequences for Arctic Council states aiming to mitigate and adapt to climate change in the north. The conclusions from our synthesis are the following. (1) Current and future Arctic fires, and the adjacent boreal region, are driven by natural (i.e. lightning) and human-caused ignition sources, including fires caused by timber and energy extraction, prescribed burning for landscape management, and tourism activities. Little is published in the scientific literature about cultural burning by Indigenous populations across the pan-Arctic, and questions remain on the source of ignitions above 70∘ N in Arctic Russia. (2) Climate change is expected to make Arctic fires more likely by increasing the likelihood of extreme fire weather, increased lightning activity, and drier vegetative and ground fuel conditions. (3) To some extent, shifting agricultural land use and forest transitions from forest–steppe to steppe, tundra to taiga, and coniferous to deciduous in a warmer climate may increase and decrease open biomass burning, depending on land use in addition to climate-driven biome shifts. However, at the country and landscape scales, these relationships are not well established. (4) Current black carbon and PM2.5 emissions from wildfires above 50 and 65∘ N are larger than emissions from the anthropogenic sectors of residential combustion, transportation, and flaring. Wildfire emissions have increased from 2010 to 2020, particularly above 60∘ N, with 56 % of black carbon emissions above 65∘ N in 2020 attributed to open biomass burning – indicating how extreme the 2020 wildfire season was and how severe future Arctic wildfire seasons can potentially be. (5) What works in the boreal zones to prevent and fight wildfires may not work in the Arctic. Fire management will need to adapt to a changing climate, economic development, the Indigenous and local communities, and fragile northern ecosystems, including permafrost and peatlands. (6) Factors contributing to the uncertainty of predicting and quantifying future Arctic fire regimes include underestimation of Arctic fires by satellite systems, lack of agreement between Earth observations and official statistics, and still needed refinements of location, conditions, and previous fire return intervals on peat and permafrost landscapes. This review highlights that much research is needed in order to understand the local and regional impacts of the changing Arctic fire regime on emissions and the global climate, ecosystems, and pan-Arctic communities.

The inaccuracy of anthropogenic emission inventories on a high-resolution scale due to insufficient basic data is one of the major reasons for the deviation between air quality model and observation results. A bottom-up approach, which is a typical emission inventory estimation method, requires a lot of human labor and material resources, whereas a top-down approach focuses on individual pollutants that can be measured directly as well as relying heavily on traditional numerical modeling. Lately, the deep neural network approach has achieved rapid development due to its high efficiency and nonlinear expression ability. In this study, we proposed a novel method to model the dual relationship between an emission inventory and pollution concentrations for emission inventory estimation. Specifically, we utilized a neural-network-based comprehensive chemical transport model (NN-CTM) to explore the complex correlation between emission and air pollution. We further updated the emission inventory based on back-propagating the gradient of the loss function measuring the deviation between NN-CTM and observations from surface monitors. We first mimicked the CTM model with neural networks (NNs) and achieved a relatively good representation of the CTM, with similarity reaching 95 %. To reduce the gap between the CTM and observations, the NN model suggests updated emissions of NOx, NH3, SO2, volatile organic compounds (VOCs) and primary PM2.5 changing, on average, by −1.34 %, −2.65 %, −11.66 %, −19.19 % and 3.51 %, respectively, in China for 2015. Such ratios of NOx and PM2.5 are even higher (∼ 10 %) in regions that suffer from large uncertainties in original emissions, such as Northwest China. The updated emission inventory can improve model performance and make it closer to observations. The mean absolute error for NO2, SO2, O3 and PM2.5 concentrations are reduced significantly (by about 10 %–20 %), indicating the high feasibility of NN-CTM in terms of significantly improving both the accuracy of the emission inventory and the performance of the air quality model.

Carbonaceous aerosol is mainly composed of organic carbon (OC) and elemental carbon (EC). Both OC and EC originate from a variety of emission sources. Radiocarbon (14C) analysis can be used to apportion bulk aerosol, OC, and EC into their sources. However, such analyses require the physical separation of OC and EC. Here, we apply of ECT9 protocol to physically isolate OC and EC for 14C analysis and evaluate its effectiveness. Several reference materials are selected, including two pure OC (fossil “adipic acid” and contemporary “sucrose”), two pure EC (fossil “regal black” and “C1150”), and three complex materials containing contemporary and/or fossil OC and EC (“rice char”, NIST urban dust standards “SRM1649a” and “SRM8785”, i.e., fine fraction of resuspended SRM1649a on filters). The pure materials were measured for their OC, EC, and total carbon (TC) mass fractions and corresponding carbon isotopes to evaluate the uncertainty of the procedure. The average accuracy of TC mass, determined via volumetric injection of a sucrose solution, was approximately 5 %. Ratios of EC/TC and OC/TC were highly reproducible, with analytical precisions better than 2 % for all reference materials, ranging in size from 20 to 100 µg C. Consensus values were reached for all pure reference materials for both δ13C and fraction modern (F14C), with an uncertainty of < 0.3 ‰ and approximately 5 %, respectively. The procedure introduced 1.3 ± 0.6 µg of extraneous carbon, an amount compatible to that of the Swiss_4S protocol. In addition, OC and EC were isolated from mixtures of pure contemporary OC (sucrose) with pure fossil EC (regal black) and fossil OC (adipic acid) with contemporary EC (rice char EC) to evaluate the effectiveness of OC and EC separation. Consensus F14C values were reached for all OC (∼ 5–30 µg) and EC (∼ 10–60 µg) fractions with an uncertainty of ∼ 5 % on average. We found that the ECT9 protocol efficiently isolates OC or EC from complex mixtures. Based on δ13C measurements, the average contribution of charred OC to EC is likely less than 3 % when the OC loading amount is less than 30 µg C. Charring was further assessed by evaluating thermograms of various materials, including aerosol samples collected in the Arctic and from tailpipes of gasoline or diesel engines. These data demonstrate that the ECT9 method effectively removes pyrolyzed OC. Thus, the ECT9 protocol, initially developed for concentration and stable isotope measurements of OC and EC, is suitable for 14C-based apportionment studies, including µg C-sized samples from arctic environments.

In recent years, ozone pollution has become one of the most severe environmental problems in China. Evidence from observations have showed increased frequency of high O3 levels in suburban areas of the Yangtze River Delta (YRD) region. To better understand the formation mechanism of local O3 pollution and investigate the potential role of isoprene chemistry in the budgets of ROx (OH+HO2+RO2) radicals, synchronous observations of volatile organic compounds (VOCs), formaldehyde (HCHO), and meteorological parameters were conducted at a suburban site of the YRD region in 2018. Five episodes with elevated O3 concentrations under stagnant meteorological conditions were identified; an observation-based model (OBM) with the Master Chemical Mechanism was applied to analyze the photochemical processes during these high O3 episodes. The high levels of O3, nitrogen oxides (NOx), and VOCs facilitated strong production and recycling of ROx radicals with the photolysis of oxygenated VOCs (OVOCs) being the primary source. Our results suggest that local biogenic isoprene is important in suburban photochemical processes. Removing isoprene could drastically slow down the efficiency of ROx recycling and reduce the concentrations of ROx. In addition, the absence of isoprene chemistry could further lead to a decrease in the daily average concentrations of O3 and HCHO by 34 % and 36 %, respectively. Therefore, this study emphasizes the importance of isoprene chemistry in the suburban atmosphere, particularly with the participation of anthropogenic NOx. Moreover, our results provide insights into the radical chemistry that essentially drives the formation of secondary pollutants (e.g., O3 and HCHO) in suburban areas of the YRD region.

As our knowledge and understanding of atmospheric aerosol particle evolution and impact grows, designing community mechanistic models requires an ability to capture increasing chemical, physical and therefore numerical complexity. As the landscape of computing software and hardware evolves, it is important to profile the usefulness of emerging platforms in tackling this complexity. Julia is a relatively new programming language that promises computational performance close to that of Fortran, for example, without sacrificing the flexibility offered by languages such as Python. With this in mind, in this paper we present and demonstrate the initial development of a high-performance community mixed-phase atmospheric 0D box model, JlBox, written in Julia. In JlBox v1.1 we provide the option to simulate the chemical kinetics of a gas phase whilst also providing a fully coupled gas-particle model with dynamic partitioning to a fully moving sectional size distribution, in the first instance. JlBox is built around chemical mechanism files, using existing informatics software to parse chemical structures and relationships from these files and then provide parameters required for mixed-phase simulations. In this study we use mechanisms from a subset and the complete Master Chemical Mechanism (MCM). Exploiting the ability to perform automatic differentiation of Jacobian matrices within Julia, we profile the use of sparse linear solvers and pre-conditioners, whilst also using a range of stiff solvers included within the expanding ODE solver suite the Julia environment provides, including the development of an adjoint model. Case studies range from a single volatile organic compound (VOC) with 305 equations to a “full” complexity MCM mixed-phase simulation with 47 544 variables. Comparison with an existing mixed-phase model shows significant improvements in performance for multi-phase and mixed VOC simulations and potential for developments in a number of areas.

A 1:15 3/4 open-jet scaled wind tunnel was used for experimental test. By arranging the synthetic jet actuator around the nozzle, the experimental method was used to analyze the flow field after the active flow control was implemented. The effects of the excitation frequency fJ of different input signals and the excitation velocity V0 of different jet nozzles on the jet shear layer and the flow field in the test section were studied. The obtained results showed that when the excitation frequency of the synthetic jet actuator (fJ) was 40 Hz and excitation velocity (V0) equaled to 10 m/s, the turbulence intensity of each measurement point was the highest among all excitation frequencies, and the flow field had a peak near 19–20 Hz, which was the sensitive frequency of buffeting. The highest power spectral density of this frequency peak was nearly ten times higher than the original working condition, which meant that this control scheme will aggravate the buffeting phenomenon. For fJ = 140 Hz and V0 = 15 m/s, it only had a high PSD peak at 19–20 Hz near the measurement point 15 of the collector. The overall control effect of this scheme is better than other schemes. Therefore, it can significantly suppress the buffeting phenomenon of the wind tunnel and improve the flow field quality of the test section.

The North Sea is Europe's key oil and gas (O&G) basin with the output currently meeting 3 %–4 % of global oil supply. Despite this, there are few observational constraints on the nature of atmospheric emissions from this region, with most information derived from bottom-up inventory estimates. This study reports on airborne measurements of volatile organic compounds (VOCs) emitted from O&G-producing regions in the North Sea. VOC source emission signatures for the primary extraction products from offshore fields (oil, gas, condensate, mixed) were determined in four geographic regions. Measured iso-pentane to n-pentane (iC5 / nC5) ratios were 0.89–1.24 for all regions, used as a confirmatory indicator of O&G activities. Light alkanes (ethane, propane, butane, pentane) were the dominant species emitted in all four regions; however, total OH reactivity was dominated by unsaturated species, such as 1,3-butadiene, despite their relatively low abundance. Benzene to toluene ratios indicated the influence of possible terrestrial combustion sources of emissions in the southern, gas-producing region of the North Sea, seen only during south or south-westerly wind episodes. However, all other regions showed a characteristic signature of O&G operations. Correlations between ethane (C2H6) and methane (CH4) confirmed O&G production to be the primary CH4 source. The enhancement ratio (ΔC2H6/ΔCH4) ranged between 0.03–0.18, indicating a spatial dependence on emissions with both wet and dry CH4 emission sources. The excess mole fraction demonstrated that deepwater oil extraction resulted in a greater proportion of emissions of higher carbon number alkanes relative to CH4, whereas gas extraction, typically from shallow waters, resulted in a less complex mix of emissions dominated by CH4. The VOC source profiles measured were similar to those in the UK National Atmospheric Emissions Inventory (NAEI) for oil production, with consistency between the molar ratios of light alkanes to propane. The largest discrepancies between observations and the inventory were for mono-aromatic compounds, highlighting that these species are not currently fully captured in the inventory. These results demonstrate the applicability of VOC measurements to distinguish unique sources within the O&G sector and give an overview of VOC speciation over the North Sea.