Long-term Continuous Observation Research Articles

Comprehensive quantitative determination of aquifer confinement based on tidal response of well water level and its application in North China

Aquifer confinement represents a pivotal property that significantly influences the vulnerability and contamination risk of groundwater resources. Several methods have been proposed for determining aquifer confinement by analyzing the response of well water level to Earth tides and atmospheric tides. In this study, we evaluated the performance of the existing single methods and put forward an optimized comprehensive approach. We compared the determination results of the three single methods with those of a comprehensive method using water-level data from 39 earthquake precursor monitoring wells in North China. The results demonstrate that the comprehensive method effectively determined aquifer confinement, significantly reducing the uncertainty associated with the three single methods. The application of the comprehensive method in North China reveals that aquifer confinement may undergo temporal variations during long-term continuous observation, especially in areas where the confining properties of aquifers may vary due to human activities and earthquakes. In such areas, the comprehensive method facilitates accurate assessment of groundwater vulnerability, as well as the potential dispersion of underground pollutants.

Pollution characteristics, sources, and health risks of phthalate esters in ambient air: A daily continuous monitoring study in the central Chinese city of Nanchang

In recent years, the atmospheric pollution caused by phthalate esters (PAEs) has been increasing due to the widespread use of PAE-containing materials. Existing research on atmospheric PAEs lacks long-term continuous observation and samples from cities in central China. To investigate the pollution characteristics, sources, and health risks of PAEs in the ambient air of a typical city in central China, daily PM2.5 samples were collected in Nanchang from November 2020 to October 2021. In this study, the detection and quantification of six significant PAE contaminants, namely diethyl phthalate (DEP), di-n-butyl phthalate (DnBP), diisobutyl phthalate (DIBP), Di-2-ethylhexyl phthalate (DEHP), di-n-octyl phthalate (DnOP), and diisodecyl phthalate (DIDP), were accomplished using gas chromatography and mass spectrometry. The results revealed that the concentrations of DEP, DnBP, DEHP, and DnOP were relatively high. Higher temperatures promote the volatilization of PAEs, leading to an increase in the gaseous and particulate PAE concentrations in warm seasons and winter pollution scenarios. The results of principal component analysis show that PAEs mainly come from volatile products and polyvinylchloride plastics. Using positive matrix factorization analysis, it is shown that these two sources contribute 67.0% and 33.0% in atmosphere PAEs, respectively. Seasonally, the contribution of volatile products to both gaseous and particulate PAEs substantially increases during warm seasons. The residents in Nanchang exposed to PAEs have a negligible non-cancer risk and a potential low cancer risk. During the warm seasons, more PAEs are emitted into the air, which will increase the toxicity of PAEs and their impact on human health.

Intercomparison of leaf area index observed by destructive sampling, plant canopy analyzer and tracing radiation and architecture of canopies in paddy fields

ABSTRACT Leaf area index (LAI) is a canopy structure parameter used to characterize vegetation growth. It is increasingly important to obtain continuous and accurate ground LAI measurement data for the validation of remote-sensing products. In this study, direct destructive sampling method and indirect optical measurement including LAI-2200 plant canopy analyser (PCA) and Tracing Radiation and Architecture of Canopies (TRAC) were used for long-term continuous observation of paddy fields in southern China, to explore the variation of LAI during the growth period of paddy, and to quantitatively analyse the errors of indirect optical measurement. The results show that (1) LAI and Plant area index (PAI) increased first and then decreased in the growing period. The proportion of green leaf area gradually decreased at reproductive growth stage (less than 50%). There was a linear relationship between the proportion of green leaf area and PAI at this stage, with a good correlation (R2 = 0.73). This linear relationship can be used to convert PAI into LAI more conveniently. (2) Effective PAI (PAIe) calculated by the two methods (2000 method and Lang method) from PCA showed good consistency between each other in the growing season (the maximum value of R2 is 0.99). With the increase of zenith angle, the consistency between 2000 method and Lang method decreases (R2 = 0.83). Multiple scattering has an effect on PCA measurement, and this effect is more obvious at high zenith angle. Lang method is more sensitive to the change of zenith angle. (3) Compared to the destructive values, both 2000 method and Lang method are able to compute accurate LAI using four ring sensors (4 R), while TRAC underestimates the LAI and PAI from destructive sampling method. This study provided a new idea for reducing the impact of ground reference data errors on LAI product validation.

Evaluation of in situ observations on Marine Weather Observer during Typhoon Sinlaku

Abstract. The mobile ocean weather observation system, named Marine Weather Observer (MWO), developed by the Institute of Atmospheric Physics (IAP), consists of a fully solar-powered, unoccupied vehicle and meteorological and hydrological instruments. One of the MWOs completed a long-term continuous observation, actively approaching the center of Typhoon Sinlaku from 24 July to 2 August 2020, over the South China Sea. The in situ and high-temporal-resolution (1 min) observations obtained from MWO were analyzed and evaluated through comparison with the observations made by two types of buoys during the evolution of Typhoon Sinlaku. First, the air pressure and wind speed measured by MWO are in good agreement with those measured by the buoys before the typhoon, reflecting the equivalent measurement capabilities of the two methods under normal sea conditions. The sea surface temperature (SST) between MWO and the mooring buoys is highly consistent throughout the observation period, indicating the high stability and accuracy of SST measurements from MWO during the typhoon evolution. The air temperature and relative humidity measured by MWO have significant diurnal variations, generally lower than those measured by the buoys, which may be related to the mounting height and sensitivity of sensors. When actively approaching the typhoon center, the air pressure from MWO can reflect some drastic and subtle changes, such as a sudden drop to 980 hPa, which is difficult to obtain by other observation methods. As a mobile meteorological and oceanographic observation station, MWO has shown its unique advantages over traditional observation methods, and the results preliminarily demonstrate the reliable observation capability of MWO in this paper.

Structure design and implementation of a high stability semi-submersible optical buoy for marine environment observation

Marine optical buoys are recognized as highly effective technical means for obtaining long-term continuous ocean optical observation data for on-orbit ocean color satellite radiometric calibration and remote sensing product validation. The high stability of a buoy's body structure is a crucial factor for marine optical buoys to operate in complex environments, such as in the presence of wind, waves, and currents. In this study, we propose a highly stable self-counterweight transverse-tethered semi-submersible buoy structure achieved through buoy structure design, mooring system design, mechanical analysis and numerical simulation analysis, and transverse-tethered point analysis. The novel buoy design underwent a marine environment adaptability test, demonstrating an improved ability to resist wind and waves while also greatly reducing the difficulty and cost of design and deployment. In-situ verification showed that the buoy's swing angle was better than ±10° under a 3–4 level sea state, meeting marine optical buoy requirements and proving the new buoy design suitable for harsh and complex marine conditions.

Long-term variation, solubility and transport pathway of PM2.5-bound iron in a megacity of northern China

Although particulate Fe has a significant impact on human health, atmospheric chemical reactions, air quality, climate change, and ecosystems, there is a lack of long-term continuous hourly observation on particulate Fe in the megacity of Beijing, limiting research on these issues. To address this gap, this study continuously measured hourly concentrations of Fe in PM2.5 from October 2018 to October 2022 in Beijing. The results indicate an overall decline in Fe concentrations, consistent with previous studies in Beijing. This decline can be attributed to multiple factors, such as reduced coal consumption, restrictions on biomass burning, increased use of clean energy, advanced technologies for industrial emission reduction, and efforts to control fugitive dust. Seasonal variations in Fe concentrations were similar across the various years, with higher mean concentrations in spring, fall, and winter, and lower levels in summer. Daily variations in PM2.5-bound Fe concentrations exhibited two peaks, influenced by changes in emission intensity and the evolution of the planetary boundary layer. The solubility of PM2.5-bound Fe exhibited a wide range, varying from 4 % to 95 %, surpassing previously reported source-specific values. This variability can be attributed to acid dissolution effects and complexation behaviors. Nonparametric wind regression analysis identified distinct hotspots (higher concentrations) in the northwest wind sector at wind speeds of approximately 5–15 km/h, which are associated with blowing dust and dust storms. Additionally, the potential source contribution function analysis identified high-potential source areas were precisely located in the northwestern, western, and southern regions of Beijing, rather than primarily in the southern areas recorded in a previous study. This research provides valuable insights for studying the health effects and migration and transformation of nutrient elements, particularly particulate Fe, in Beijing.

Screening Station, a novel laboratory automation system for physiologically relevant cell-based assays.

Due to their physiological relevance, cell-based assays using human-induced pluripotent stem cell (iPSC)-derived cells are a promising in vitro pharmacological evaluation system for drug candidates. However, cell-based assays involve complex processes such as long-term culture, real-time and continuous observation of living cells, and detection of many cellular events. Automating multi-sample processing through these assays will enhance reproducibility by limiting human error and reduce researchers' valuable time spent conducting these experiments. Furthermore, this integration enables continuous tracking of morphological changes, which is not possible with the use of stand-alone devices. This report describes a new laboratory automation system called the Screening Station, which uses novel automation control and scheduling software called Green Button Go to integrate various devices. To integrate the above-mentioned processes, we established three workflows in Green Button Go: 1) For long-term cell culture, culture plates and medium containers are transported from the automatic CO2 incubator and cool incubator, respectively, and the cell culture medium in the microplates is exchanged daily using the Biomek i7 workstation; 2) For time-lapse live-cell imaging, culture plates are automatically transferred between the CQ1 confocal quantitative image cytometer and the SCALE48W automatic CO2 incubator; 3) For immunofluorescence imaging assays, in addition to the above-mentioned devices, the 405LS microplate washer allows for formalin-fixation and immunostaining of cells. By scheduling various combinations of the three workflows, we successfully automated the culture and medium exchange processes for iPSCs derived from patients with facioscapulohumeral muscular dystrophy, confirmation of their differentiation status by live-cell imaging, and confirmation of the presence of differentiation markers by immunostaining. In addition, deep learning analysis enabled us to quantify the degree of iPSC differentiation from live-cell imaging data. Further, the results of the fully automated experiments could be accessed via the intranet, enabling experiments and analysis to be conducted remotely once the necessary reagents and labware were prepared. We expect that the ability to perform clinically and physiologically relevant cell-based assays from remote locations using the Screening Station will facilitate global research collaboration and accelerate the discovery of new drug candidates.

Continuous, long-term crawling behavior characterized by a robotic transport system.

Detailed descriptions of behavior provide critical insight into the structure and function of nervous systems. In Drosophila larvae and many other systems, short behavioral experiments have been successful in characterizing rapid responses to a range of stimuli at the population level. However, the lack of long-term continuous observation makes it difficult to dissect comprehensive behavioral dynamics of individual animals and how behavior (and therefore the nervous system) develops over time. To allow for long-term continuous observations in individual fly larvae, we have engineered a robotic instrument that automatically tracks and transports larvae throughout an arena. The flexibility and reliability of its design enables controlled stimulus delivery and continuous measurement over developmental time scales, yielding an unprecedented level of detailed locomotion data. We utilize the new system's capabilities to perform continuous observation of exploratory search behavior over a duration of 6 hr with and without a thermal gradient present, and in a single larva for over 30 hr. Long-term free-roaming behavior and analogous short-term experiments show similar dynamics that take place at the beginning of each experiment. Finally, characterization of larval thermotaxis in individuals reveals a bimodal distribution in navigation efficiency, identifying distinct phenotypes that are obfuscated when only analyzing population averages.

Increasing NH3 Emissions in High Emission Seasons and Its Spatiotemporal Evolution Characteristics during 1850–2060

Ammonia (NH3) is a crucial alkaline component in the atmosphere, with significant impacts on environmental and ecosystem health. However, our understanding of the long-term variability characteristics of NH3 emissions is still limited due to the scarcity of long-term continuous NH3 emission observation data. In this study, we investigated the global NH3 emission evolution pattern during the high-emission season (March–August) in historical (1850–2014) and future (2015–2060) periods, based on the simulated global NH3 emission and temperature data using the CESM2-WACCM model from CMIP6. We utilized cluster analysis, KNN regression simulation, and transfer matrix analysis to explore the emission characteristics. In the historical period, the analysis revealed that the high NH3 emission season is March–August, accounting for about 60% of annual emissions, with a significant increasing trend of NH3 emissions. The global average NH3 emissions in the last 164 years were about four times higher (28.06 mg m−2) than those in 1850 (5.52 mg m−2). Moreover, on the intercontinental scale, NH3 emissions from 1850 to 2014 March–August exhibited dynamic increases characterized differently across continents. Europe showed an increasing and then decreasing trend, Asia demonstrated a rapid increase, while South America, North America, and Africa exhibited medium increases, and Australia showed low increases. The global NH3 emissions experienced three distinct periods of low (1850–1964, slope = 0.059 mg m−2 y−1), high (1965–1988, slope = 0.389 mg m−2 y−1), and medium (1989–2014, slope = 0.180 mg m−2 y−1) rates of increase. Starting from the high rate of increase period, the hotspots of global NH3 emissions gradually shifted from Europe to East and South Asia. Looking ahead, our findings suggest that the global NH3 emission rate will tend to slow down under the Representative Concentration Pathway (RCP) 4.5 and RCP8.5 warming scenarios. However, compared with the medium-rate increasing period, the moderate and heavy NH3 emission areas under RCP4.5 and RCP8.5 scenarios will show a tendency to expand by 2060, with the proportion of area covered by heavy emissions increasing by 0.55% and 0.56%, respectively. In conclusion, our study highlights that NH3 pollution remains a significant environmental challenge in the future period, with Asia and Europe being the key areas requiring attention for NH3 emission reduction.

Assessment of S-net seafloor pressure data quality in view of seafloor geodesy

Long-term continuous observation of seafloor pressure is effective for detecting seafloor vertical deformations that are associated with transient tectonic phenomena such as slow slip events. Since the aseismic slip event prior to the 2011 Tohoku earthquake, several discoveries have been made on spontaneous slow slip events and various other types of slow earthquake along the Japan and Kuril Trenches. Seafloor observation network for earthquakes and tsunamis along the Japan Trench (S-net) is expected to provide invaluable information on slow slip activities via geodetic signals that are detected by pressure observation. This study inspects the quality of the S-net pressure data in view of seafloor geodesy by comparison with records obtained by more than 100 autonomous ocean bottom pressure recorders (OBPRs) deployed along the Japan Trench. OBPRs have long been standard tools in seafloor geodesy, and the data collected are considered a benchmark in terms of quality. Most of the S-net stations showed noise levels that are considerably higher than those of the OBPRs over periods of more than 2 d. We speculate that a strong correlation between pressure and temperature accounts for much of the long-term noise. In this study, the temperature-dependent fluctuation component was estimated by prediction filtering and removed from the original data, leading to a significant reduction in the noise level at 51 stations, which reached levels almost equivalent to those of OBPRs. Although no significant pressure changes have been identified as associated with the 2018 Boso SSE or repeated tremor bursts in the northern Japan Trench thus far, our findings indicate that these stations are sufficiently sensitive to detect slow slip events occurring nearby.

Emission of Nitrous Oxide (N2O) from Lake Taihu and the Corresponding Potential Driving Factors

Nitrous oxide (N2O) is one of the six greenhouse gases stipulated in the Kyoto Protocol. Its greenhouse potential over the past century was 298 times that of CO2, and the concentration of atmospheric N2O has been continuously and rapidly increasing during the past hundred years. Shallow lakes are an important source of atmospheric N2O. In order to explore the temporal and spatial changes and potential driving factors of N2O emissions from eutrophic water, we conducted field observations in February (winter) and August (summer) in Lake Taihu. We used the coefficient of diffusion-headspace bottle method to trace the variability in the N2O concentration[c(N2O)] and efflux[F(N2O)] from surface water bodies and explored the potential driving factors of N2O emissions. The optical measurements of dissolved organic matter (DOM) are an effective approach for tracing the source and composition of dissolved organic carbon (DOC) and dissolved organic nitrogen (DON). The migration and transformation processes of DOM also release a large amount of inorganic nitrogen, which changes the redox potential of the water column and thereby affects N2O emissions. Our results showed that the variability in c(N2O) and F(N2O) in the surface waters of Lake Taihu were strongly affected by water temperature and nutrient levels. The average c(N2O) of the surface waters was (19.7±2.7) nmol·L-1, corresponding to a mean F(N2O) of (41.1±1.8) μmol·(m2·d)-1, and the means of both c(N2O) and F(N2O) were higher in summer than those in winter (t-test, P<0.01). The input and accumulation of DOM could increase the production and emission potential of N2O in water bodies, as supported by both c(N2O) and F(N2O) significantly increasing with increasing level of terrestrial humic-like C1. The integration ratio of peak C to peak T IC:IT of DOM and the spectral slope S275-295 results indicated that there were high inputs of terrestrial DOM in the northwestern inflowing river mouths, concurring with the high production and emission of N2O found there. This suggested that the accumulation and degradation of terrestrial DOM potentially fueled the emission of N2O. Our results showed that water temperature, DOM composition, and nutrient level were all important factors affecting N2O emission from Lake Taihu. Long-term continuous observation can be applied to better evaluate the impact of various environmental factors on the production and emission of N2O in water bodies and to help with providing scientific emission reduction plans.

The succession of submerged vegetation in the northern part of Lake Fuxian and its ecological indication significance(1987-2020)

抚仙湖有近210亿m³的优质淡水资源，具有重要战略价值，但是近年来出现水质退化的现象.沉水植被是湖泊生态系统功能维持的重要生物门类，其演变过程能反映和影响整个生态系统的变化，目前还缺乏对抚仙湖沉水植被长期连续地观测记录.本文基于Landsat遥感数据分析了抚仙湖北部沉水植被面积的动态变化，结合气候变化和水质水文要素分析发现：抚仙湖北部湖区沉水植物在1987—2020年间存在先减少后增加的变化趋势；1987—1995年，沉水植物分布面积约占北部湖区面积的1.64%；1996—2010年北部湖区沉水植被分布面积缩减，湖泊处于高水位低营养状态，水位上升是此时期沉水植物面积减少的主要原因；2011—2020年，水位降低，营养增加，营养和水位的共同作用导致抚仙湖北部湖区沉水植物面积显著增加.沉水植物覆盖度变化伴随着沉水植被以苦草为优势种群转为以穗花狐尾藻为优势种群，沉水植被结构转向耐污染性更强的属种.通过抚仙湖北部湖区沉水植被发育与营养、水位等驱动因子的关系分析，建议现阶段需要严格限制入湖氮磷排放，强化水生植被的长期动态监测，构建水量、水质、水生态一体化监测体系，并开展抚仙湖生态系统演变的模拟和预测，防止抚仙湖生态系统出现突变，以维持抚仙湖生态系统功能多样性.;Lake Fuxian has nearly 21 billion cubic meters of high-quality freshwater resources which has important strategic value, but the water quality has been degraded in recent years. Submerged vegetation is an important biological category for the function maintenance of the lake ecosystem, and its succession can reflect and influence the changes of the whole ecosystem. At present, there is a lack of long-term continuous observation records of submerged vegetation in Lake Fuxian. Based on Landsat remote sensing data, this paper analyzes the dynamic changes of submerged vegetation in the northern part of Lake Fuxian. Integrating climate change and water quality hydrological elements, submerged vegetation in the northern part of Lake Fuxian showed a decrease followed by an increase from 1987 to 2020. From 1987 to 1995, the distribution area of submerged vegetation accounted for about 1.64% of the northern lake area. From 1996 to 2010, the submerged vegetation in the northern lake area reduced, and the lake was in a state of high water level and low nutrients. The rise of the water level was the main reason for the reduction of submerged vegetation area during this period. From 2011 to 2020, the water level decreased and nutrients increased, and the combined effect of nutrients and water level led to a significant increase in the area of submerged vegetation in the northern lake area of Lake Fuxian. The change in submerged vegetation coverage was accompanied by a shift in submerged vegetation from Vallisneria natans as the dominant population to Myriophyllum spicatum as the dominant population, and the structure of submerged vegetation turns into more pollution-tolerant species. In this study, the analysis of the relationship between the development of submerged vegetation and the driving factors such as nutrients and water level in the north of Lake Fuxian suggests that at this stage, it is necessary to strictly restrict the discharge of nitrogen and phosphorus into the lake, strengthen the long-term dynamic monitoring of aquatic vegetation, build an integrated monitoring system for water quantity, quality and ecology, and carry out simulation and prediction of the Lake Fuxian ecosystem change to prevent Lake Fuxian ecosystem from regime shifts and maintain its functional diversity Lake Fuxian.

Application Of Electrical Ship Wakes Detection Trace of Synthetic Aperture Radar (SAR) Image in Coast Guard

The current situation of rights protection of the coast guard in China is lack of the monitoring capacity especially in a wide range using the ship-borne equipment. Compared with shore-based, ship-borne, airborne detection devices, visible light and infrared remote sensing, SAR has the advantages of coverage widely, stable platform, long-term continuous observation and high input-output ratio. The common methods of ship information extraction based on SAR images include direct detection of ship targets, detection of ship wake characteristics and detection of oil film on sea surface caused by engine or fish oil leakage. Several algorithms have been developed for ship wake detection, including two-parameter constant false alarm rate (CFAR) algorithm, K-distribution based CFAR algorithm, multi-polarization detection algorithm and multi-image correlation method. In this paper, combining the needs of marine rights enforcement and analyzing the characteristics of different algorithms and, the ship wake information extraction technology of SAR image is applied to the marine integrated management and control network to improve the recognition rate of ship target monitoring, expand the monitoring scope, shorten the analysis and recognition time, and effectively enhance the law enforcement capability of marine rights protection in China. Strength, safeguard China's marine rights and interests.

Long-term water use characteristics and patterns of typical tree species in seasonal drought regions

In the areas with seasonal drought, water is the key factor affecting plant growth and development. Based on long-term continuous observation data, it is of great significance to explore plant water use patterns for vegetation construction in areas with seasonal drought. Taking Platycladus orientalis in Beijing mountainous area as the research object, stable hydrogen and oxygen isotope technique was applied to measure the isotopic composition of water from the soil, plant branches, and precipitation from 2012 to 2017. The relative contribution of soil water from different soil layers to P. orientalis was quantified by the MixSIAR model. The results showed that soil water in the deep layer (40-100 cm) was more stable than that in the shallow layer (0-40 cm). The variation of soil water content and water isotope values in the shallow layer were more obvious due to the effects of evaporation and precipitation. P. orientalis mainly absorbed stable deep soil water, with a relative contribution rate of 55.7%. In the dry season, with the decreases of soil water content, the absorption depth of plants to soil water gradually shifted to the shallow layer. Under conditions of moist, natural condition, mild drought and moderate drought, the relative contribution rates of deep soil water were 59.8%, 57.9%, 54.6%, 52.7%, respectively. To maintain higher transpiration in the wet season, P. orientalis relied more on deep soil water under mild and moderate drought conditions than in the dry season. Under the conditions of moist, natural condition, mild drought and moderate drought, the relative contribution rates of deep soil water were 58.9%, 57.6%, 56.4%, and 57.1%, respectively. The adaptive characteristic of P. orientalis, which adjusts the depth of root water absorption according to soil moisture condition, is of great significance for tree species selection in ecological afforestation and long-term management planning in areas with seasonal drought.

Initial Results of Long-term Continuous Observation of Lightning Discharges by FALMA in Chinese Inland Plateau Region

We started a long-term continuous observation of lightning discharges in the Chinese inland plateau region using a fast antenna lightning mapping array (FALMA). During the first year of observation, 2019, we recorded lightning discharges on 25 days in Yinchuan city, the capital of Ningxia. Most of the lightning discharges appeared to occur in the afternoons of individual thunderstorm days in August. We studied the cloud-to-ground (CG) flash percentages, lightning discharge source spatiotemporal distributions, and preliminary breakdown (PB) process characteristics for the two thunderstorm cases that produced the most frequent lightning flashes in 2019 over a wide area. It was found that (1) CG flashes in these two thunderstorms accounted for 28.4% and 32.5% of total lightning flashes, respectively; (2) most lightning discharge sources in these two thunderstorms occurred at temperatures between 5 and −30 °C, with a peak at around −10 °C; and (3) more than 90% of well-mapped PB processes of intracloud (IC) flashes propagated downward. By overlapping the altitudes and the progression directions of the PB processes on the lightning source spatiotemporal distributions, we inferred that the main negative charge of the two storms observed in Ningxia, China, was at a height of around −15 to −25 °C (7 to 9 km) and the main positive charge was at a height of around 5 to 0 °C (2 to 4 km).

IAP’s Solar-Powered Unmanned Surface Vehicle Actively Passes through the Center of typhoon Sinlaku (2020)

The solar-powered marine unmanned surface vehicle (USV) developed by the USV team of the Institute of Atmospheric Physics is a rugged, long-duration, and autonomous navigation vessel designed for the collection of long-range, continuous, real-time, meteorological and oceanographic measurements, especially under extreme sea conditions (sea state 6–7). These solar-powered USVs completed a long-term continuous navigation observation test over 26 days. During this time, they coordinated double-USV observations and actively navigated into the path of Typhoon Sinlaku (2020) before collecting data very close to its center during the 2020 USV South China Sea Typhoon Observation Experiment. Detailed high temporal resolution (1 min) real-time observations collected by the USV on the typhoon were used for operational typhoon forecasting and warning for the first time. As a mobile meteorological and oceanographic observation station capable of reliable, automated deployment, data collection, and transmission, such solar-powered USVs can replace traditional observation platforms to provide valuable real-time data for research, forecasting, and early warnings for potential marine meteorological disasters.

Modelling Patient Behaviour Using IoT Sensor Data: a Case Study to Evaluate Techniques for Modelling Domestic Behaviour in Recovery from Total Hip Replacement Surgery

The UK health service sees around 160,000 total hip or knee replacements every year and this number is expected to rise with an ageing population. Expectations of surgical outcomes are changing alongside demographic trends, whilst aftercare may be fractured as a result of resource limitations. Conventional assessments of health outcomes must evolve to keep up with these changing trends. Health outcomes may be assessed largely by self-report using Patient Reported Outcome Measures (PROMs), such as the Oxford Hip or Oxford Knee Score, in the months up to and following surgery. Though widely used, many PROMs have methodological limitations and there is debate about how to interpret results and definitions of clinically meaningful change. With the development of a home-monitoring system, there is opportunity to characterise the relationship between PROMs and behaviour in a natural setting and to develop methods of passive monitoring of outcome and recovery after surgery. In this paper, we discuss the motivation and technology used in long-term continuous observation of movement, sleep and domestic routine for healthcare applications, such as the HEmiSPHERE project for hip and knee replacement patients. In this case study, we evaluate trends evident in data of two patients, collected over a 3-month observation period post-surgery, by comparison with scores from PROMs for sleep and movement quality, and by comparison with a third control home. We find that accelerometer and indoor localisation data correctly highlight long-term trends in sleep and movement quality and can be used to predict sleep and wake times and measure sleep and wake routine variance over time, whilst indoor localisation provides context for the domestic routine and mobility of the patient. Finally, we discuss a visual method of sharing findings with healthcare professionals.

Global retrieval of phytoplankton functional types based on empirical orthogonal functions using CMEMS GlobColour merged products and further extension to OLCI data

This study presents an algorithm for globally retrieving chlorophyll a (Chl-a) concentrations of phytoplankton functional types (PFTs) from multi-sensor merged ocean color (OC) products or Sentinel-3A (S3) Ocean and Land Color Instrument (OLCI) data from the GlobColour archive in the frame of the Copernicus Marine Environmental Monitoring Service (CMEMS). The retrieved PFTs include diatoms, haptophytes, dinoflagellates, green algae and prokaryotic phytoplankton. A previously proposed method to retrieve various phytoplankton pigments, based on empirical orthogonal functions (EOF), is investigated and adapted to retrieve Chl-a concentrations of multiple PFTs using extensive global data sets of in situ pigment measurements and matchups with satellite OC products. The performance of the EOF-based approach is assessed and cross-validated statistically. The retrieved PFTs are compared with those derived from diagnostic pigment analysis (DPA) based on in situ pigment measurements. Results show that the approach predicts well Chl-a concentrations of most of the mentioned PFTs. The performance of the approach is, however, less accurate for prokaryotes, possibly due to their general low variability and small concentration range resulting in a weak signal which is extracted from the reflectance data and corresponding EOF modes. As a demonstration of the approach utilization, the EOF-based fitted models based on satellite reflectance products at nine bands are applied to the monthly GlobColour merged products. Climatological characteristics of the PFTs are also evaluated based on ten years of merged products (2002−2012) through inter-comparisons with other existing satellite derived products on phytoplankton composition including phytoplankton size class (PSC), SynSenPFT, OC-PFT and PHYSAT. Inter-comparisons indicate that most PFTs retrieved by our study agree well with previous corresponding PFT/PSC products, except that prokaryotes show higher Chl-a concentration in low latitudes. PFT dominance derived from our products is in general well consistent with the PHYSAT product. A preliminary experiment of the retrieval algorithm using eleven OLCI bands is applied to monthly OLCI products, showing comparable PFT distributions with those from the merged products, though the matchup data for OLCI are limited both in number and coverage. This study is to ultimately deliver satellite global PFT products for long-term continuous observation, which will be updated timely with upcoming OC data, for a comprehensive understanding of the variability of phytoplankton composition structure at a global or regional scale.

Applicability of Doppler LiDAR to Long-term Continuous Observation of the Upper Wind

Applicability of Doppler LiDAR to Long-term Continuous Observation of the Upper Wind

太湖流域农田稻季CH4通量特征及影响因子

PDF HTML阅读 XML下载 导出引用 引用提醒 太湖流域农田稻季CH4通量特征及影响因子 DOI: 10.5846/stxb201911062340 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金面上项目（41771571）；中科院南京地理与湖泊研究所前沿探索与基础性研究（NIGLAS2016QY02）；江苏省自然资源科技项目（KJXM2019007） Characteristics and impact factors of methane flux in the paddy fields of Taihu Lake Basin Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:开展太湖流域农田稻季CH4排放研究，深入了解稻田CH4排放规律，为稻田CH4减排、制定合理稻田管理措施提供科学依据。以太湖流域稻麦轮作农田为研究区域，运用涡度相关法观测其稻季CH4通量变化，分析其通量变化特征及影响因子。结果表明：太湖流域典型稻麦轮作区稻季为CH4的源，CH4排放总量为28.95 g/m2，稻季CH4通量日变化表现为无规则型与单峰型两种模式；稻季CH4排放整体集中在水稻生长前期（81.61%）及中期（16.16%）、后期排放相对较弱（2.23%），返青期排放量较低（日均0.102 μmol m-2 s-1），分蘖期较强（日均0.451 μmol m-2 s-1），成熟期最低（日均0.006 μmol m-2 s-1）；模型所模拟的累计CH4排放通量比累计测量CH4通量低6.69%，较好地模拟了太湖流域稻田CH4的排放，土壤温度、土壤水分、土壤电导率、摩擦风速可确认为太湖流域农田稻季CH4排放的主要驱动因子。 Abstract:Methane emissions play a key role in global warming and climate change. The mechanism of methane emission in the paddy fields of the Taihu Lake Basin-a typical rice-wheat rotation region of China and also an area with one of the highest rates of land use change in the country-is still unclear, largely due to limited observation and the spatial heterogeneity of the environment. Eddy covariance, one of most popular approaches to observing methane flux, has many advantages, including long-term continuous observation, high frequency, and large monitoring range, without destruction of the original soil environment. We utilized the eddy covariance method to observe the methane flux in rice-wheat rotation paddy fields in the Taihu Lake Basin. The missing flux values were interpolated with the GA-BPNN model. The characteristics and influencing factors of methane flux were then analyzed, and a semi-empirical multiplicative model was built. The results showed that the rice-wheat rotation paddy fields were the main source of methane in the Taihu Lake Basin. During the observation period, the total amount of emitted methane was 28.95 g/m2, and methane flux values varied in the range of 0-0.861 μmol m-2 s-1. The diurnal variation in methane flux during the rice season appears under two modes:irregular and unimodal. In the irregular mode, methane flux was unstable throughout the day, and in the unimodal mode, the emissions during the day were significantly higher than that at night. The emission of methane in the rice season is concentrated in the early and middle stages of rice growth, relatively weak in the later stage, relatively low in the green stage (0.102 μmol m-2 s-1 per day), strong in the tillering stage (0.451 μmol m-2 s-1 per day), and lowest in the maturity stage (0.006 μmol m-2 s-1 per day). The results of the analysis of various impact factors are as follows:The methane flux in the rice season increased exponential with air temperature and soil temperature at 10/20/40 cm depth (R2=0.589, 0.584, 0.521, 0.459, P<0.0001). Methane flux increased with increasing temperature. Methane flux showed a weak exponential relationship with soil moisture at 10/20 cm depth (R2=0.362, 0.372, P<0.0001). With the rise in soil moisture, methane flux increased. Methane flux has a quadratic relationship with soil moisture at a depth of 40 cm (R2=0.378, P<0.0001). When the soil moisture is less than 0.41 m3 m-3, methane flux decreases with the increase in soil moisture, and when the soil moisture is greater than 0.41 m3 m-3, methane flux increased with the rise in soil moisture. Methane flux showed a power relationship with soil conductivity at 10/20/40 cm depth (R2=0.309, 0.54, 0.439, P<0.0001). As the soil conductivity increases, the methane flux increases. Methane flux and friction wind speed are only significantly correlated on a half-hour scale. The methane flux estimated by the model 2 is 6.69% lower than measured flux. The model 2 well simulates the methane emission from paddy fields in the Taihu Lake Basin. The main driving factors of methane emission from paddy fields in the Taihu Lake Basin include soil temperature, soil moisture, soil conductivity, and friction wind speed. 参考文献 相似文献 引证文献