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Abstract Vegetation Optical Depth (VOD) has emerged as a valuable metric to quantify water stress on vegetation's carbon uptake from a remote sensing perspective. However, existing spaceborne microwave remote sensing platforms face limitations in capturing the diurnal VOD variations and global products lack site‐level validation against plant physiology. To address these challenges, we leveraged the Global Navigation Satellite System (GNSS) L‐band microwave signal, measuring its attenuation by the canopy of a temperate broadleaf forest using a pair of GNSS receivers. This approach allowed us to collect continuous VOD observations at a sub‐hourly scale. We found a significant seasonal‐scale correlation between VOD and leaf water potential. The VOD diurnal amplitude is affected by soil moisture, plant transpiration and leaf surface water. Additionally, VOD can help independently estimate plant transpiration. Our findings pave the way for a deeper understanding of response of the vegetation to water stress at finer temporal scales.

Abstract Two‐dimensional transition metal dichalcogenides (TMDs) are needed in high‐performance piezoresistive sensors due to their strong strain‐induced bandgap modification and thereby large gauge factors. However, integrating a conventional high‐temperature chemical vapor deposition (CVD)‐grown TMD with a flexible substrate necessitates a transfer process that inevitably degrades the sensing properties of the TMDs and increases the overall fabrication complexity. We present a high‐performance piezoresistive strain sensor that employs large‐area PdSe2 films grown directly on polyimide (PI) substrates via plasma‐assisted selenization of a sputtered Pd film. The reliable strain transfer from the substrate to the PdSe2 film ensures an outstanding strain‐sensing capability of the sensor. Specifically, the sensors have a gauge factor of up to −315 ± 2.1, a response time under 25 ms, a detection limit of 8 × 10−6, and an exceptional stability of over 104 loading–unloading cycles. By attaching the sensors to the skin surface, we demonstrate their application for measuring physiological parameters in health care monitoring, including motion, voice, and arterial pulse vibration. Furthermore, using the PdSe2 film sensor combined with deep learning technology, we achieved intelligent recognition of artery temperature from arterial pulse signals with only a 2% difference between predicted and actual temperatures. The excellent sensing performance, together with the advantages of low‐temperature fabrication and simple device structure, make the PdSe2 film sensor promising for wearable electronics and health care sensing systems.

Abstract In this study, characteristics of charge injection under extra high electric field (above 100 kV/mm) in cross‐linked polyethylene (XLPE) were investigated by experiments of conduction current and space charge. The results show that current density from low electric field to sample breakdown corresponds to space charge limited current (SCLC) theory. More specifically, Schottky current is similar to experiment current before 100 kV/mm, while the J–E curve conforms to a modified SCLC theory after 100 kV/mm. Besides, the non‐linear coefficient of J–E curve from 100 kV/mm to extra high electric field is smaller than theoretical value, and the injection depth of space charge is restricted as the field becomes higher than 100 kV/mm, which may be caused by the negative differential mobility of charge. Driven by extra high electric field, charge collides with lattice of dielectric and scatters. As a result, mean free time of charge decreases and charge mobility is reduced with the increased field. Consequently, considering the decrease in charge mobility, a mobility‐limited charge injection equation is proposed, and the validity of the proposed equation under extra high electric field is demonstrated by space charge simulation.

Abstract Plant growth and crop harvest are impacted by both climate change and air pollution. However, their relative importance in crop yields remains elusive, especially in heavily polluted regions. Here we develop crop yield prediction models, based on a large volume of historical crop data, as well as climate and pollution records in China since 1980. A long‐term surface ozone concentration data set is developed from a machine‐learning model and various observations. An assessment of four climate and pollution factors reveals the critical role of particulate and ozone pollution in regulating interannual variations of crop yields in China. During 2010–2018, we find that the particulate pollution mitigation outweighs the negative impacts of concurrent climate change, resulting in 0.5%–1.9% net yield increases nationwide, despite of the ozone increases in the North China Plain. Looking to the future, the impacts of climate change, particularly from surface temperature increase, will dominate over pollution factors and profoundly reduce future maize and rice yields by 0.6 to 2.8% 10 yr−1 by 2050. Our findings call for attention on the threat to future global food security from the absence of pollution mitigation and the persistence of global warming.

Objective To compare the clinical efficacy of the direct anterior approach in lateral decubitus position (L‐DAA) and supine position (S‐DAA) for unilateral total hip arthroplasty. Methods A retrospective study was conducted on 89 patients who underwent primary unilateral total hip arthroplasty in our department between August 2016 and December 2017. There were 46 patients who underwent L‐DAA and 43 patients who underwent S‐DAA. The body mass index (BMI), operation time, blood loss, preoperative Hb, first day and third day postoperative Hb, incision length, hospital stay, preoperative and postoperative Harris score, preoperative and postoperative visual analogue scale (VAS) score, radiological evaluation, intraoperative and postoperative complication, postoperative absolute length difference of lower extremity were recorded and analyzed. P 0.05). However, significant differences were detected in BMI, blood loss, first day and third day postoperative Hb, and operation time (P

Abstract Form‐wound windings in electric machines designed for electric aircraft propulsion face reliability challenges due to the severe operating environment, such as high temperature and low pressure. This study proposes a forewarning method for insulation condition monitoring of form‐wound windings based on partial discharge (PD) and deep learning neural network. Three PD features are extracted from the PD profile, which provides information about physics‐of‐failure and reflects the degree of insulation degradation. An algorithm fusion extracted from auto‐encoder and long short‐term recurrent neural network is proposed to synthesize one failure precursor from these three features and make multi‐time‐step prediction through historical data to provide forewarning. An electrical and thermal accelerated ageing test is performed on the form‐wound windings at 0.2 atm to simulate working environment of electric aircraft. The proposed method is validated on the accelerated ageing dataset and shows better prediction accuracy than some existing time‐series prediction methods, indicating the advantages of the proposed method. Moreover, an on‐line hardware setup using a deep learning processor is recommended to implement the forewarning method. The proposed approach has the potential to be widely applied to other insulation systems and contribute to work on condition monitoring.

Abstract In this paper, the effect of moisture on the charge behaviour in oil‐impregnated pressboard is analysed based on the characteristics of the interface and the bulk. Space charge behaviour and infrared spectra are acquired from a sample with a high moisture content of 1.92% and another with low moisture content of 0.13%. The results show that a greater number of hydrogen bonds form in the high‐moisture sample. The threshold fields of charge injection are 1 and 0.6 kV/mm in the low‐ and high‐moisture samples, respectively. The dynamic charge transport in bulk is significantly accelerated by moisture. The drop in the injection barrier at the interface and the accelerated transport of charge in bulk in the high‐moisture sample may be associated with the mediating effect of a water layer at the interface and the lower trap energy in bulk caused by the hydrogen bonds, respectively. The combined changes in the interface and the bulk led to the dominant position of negative charges inside the high‐moisture sample, regardless of the distribution area or the charge amount.

Abstract Wetland methane (CH4) emissions comprise about one‐third of the global CH4 source. The latitudinal distribution and climate sensitivity of wetland CH4 fluxes are the key determinants of the global CH4‐climate feedback. However, large differences exist between bottom‐up estimates, informed by ground‐based flux measurements, and top‐down estimates derived from spaceborne total column CH4. Despite the extensive coverage of satellite CH4 concentration observations, challenges remain with using top‐down estimates to test bottom‐up models, mainly because of the uncertainties in the satellite retrievals, the model representation errors, the variable prior emissions, and the confounding role of the posterior error covariance structures. Here, we use satellite‐based top‐down CH4 flux estimates (2010–2012) to test and refine 42 bottom‐up estimates of wetland emissions that use a range of hypothesized wetland extents and process controls. Our comparison between bottom‐up models and satellite‐based fluxes innovatively accounts for cross‐correlations and spatial uncertainties typically found in top‐down inverse estimates, such that only the information from satellite observations and the atmospheric transport model is kept as a constraint. We present a satellite‐constrained wetland CH4 ensemble product derived from assembling the highest‐performance bottom‐up models, which estimates global wetland CH4 emissions of 148 (117–189, 5th–95th percentile) Tg CH4 yr−1. We find that tropical wetland emissions contribute 72% (63%–85%) to the global wetland total. We also find that a lower‐than‐expected temperature sensitivity agrees better with atmospheric CH4 measurements. Overall, our approach demonstrates the potential for using satellites to quantitatively refine bottom‐up wetland CH4 emission estimates, their latitudinal distributions, and their sensitivity to climate.

Abstract The livestock sector is the largest source of anthropogenic methane emissions and is projected to increase in the future with the increased demand for livestock products. Here, we compare livestock methane emissions and emission intensities, defined by the amount of methane emitted per unit of animal proteins, estimated by different methodologies, and identify mitigation potentials in different regions of the world based on possible future projections. We show that emission intensity decreased for most livestock categories globally during 2000–2018, due to an increasing protein‐production efficiency, and the IPCC Tier 2 method should be used for capturing the temporal changes in the emission intensities. We further show that efforts on the demand‐side to promote balanced, healthy, and environmentally sustainable diets in most countries will not be sufficient to mitigate livestock methane emissions without parallel efforts to improve production efficiency. The latter efforts have much greater mitigating effects than demand‐side efforts, and hence should be prioritized in a few developing countries that contribute most of the mitigation potential.

Abstract We quantify the impact of atmospheric transport and limited marine boundary layer sampling on changes in global and regional methane burdens estimate using tracer transport model simulations with annually repeating methane emissions and sinks but varying atmospheric transport patterns. We find the 1σ error due to this transport and sampling effect on annual global methane increases to be 1.11 ppb/year and on zonal growth rates to be 3.8 ppb/year, indicating that it becomes more critical at smaller spatiotemporal scales. We also find that the trends in inter‐hemispheric and inter‐polar difference of methane are significantly influenced by the effect. Contrary to a negligible trend in the inter‐hemispheric difference of measurements, we find, after adjusting for the transport and sampling, a trend of 0.37 ± 0.06 ppb/year. This is consistent with the emission trend from a 3‐D inversion of the measurements, suggesting a faster increase in emissions in the Northern Hemisphere than in the Southern Hemisphere.

Abstract Since the 1960s, carbon cycling in the high‐latitude northern forest (HLNF) has experienced dramatic changes: Most of the forest is greening and net carbon uptake from the atmosphere has increased. During the same time period, the CO2 seasonal cycle amplitude (SCA) has increased by ~50% or more. Disentangling complex processes that drive these changes has been challenging. In this study, we substitute spatial sensitivity to temperature for time to quantify the impact of temperature increase on gross primary production (GPP), total ecosystem respiration (TER), the fraction of Photosynthetic Active Radiation (fPAR), and the resulted contribution of these changes in amplifying the CO2 SCA over the HLNF since 1960s. We use the spatial heterogeneity of GPP inferred from solar‐induced chlorophyll Fluorescence in combination with net ecosystem exchange (NEE) inferred from column CO2 observations made between 2015 and 2017 from NASA's Orbiting Carbon Observatory‐2. We find that three quarters of the spatial variations in GPP can be explained by the spatial variation in the growing season mean temperature (GSMT). The long term hindcast captures both the magnitude and spatial variability of the trends in observed fPAR. We estimate that between 1960 and 2010, the increase in GSMT enhanced both GPP and the SCA of NEE by ~20%. The calculated enhancement of NEE due to increase in GSMT contributes 56–72% of the trend in the CO2 SCA at high latitudes, much larger than simulations by most biogeochemical models.

Abstract While large‐scale floods directly impact human lives and infrastructures, they also profoundly impact agricultural productivity. New satellite observations of vegetation activity and atmospheric CO2 offer the opportunity to quantify the effects of such extreme events on cropland carbon sequestration. Widespread flooding during spring and early summer 2019 induced conditions that delayed crop planting across the U.S. Midwest. As a result, satellite observations of solar‐induced chlorophyll fluorescence from TROPOspheric Monitoring Instrument and Orbiting Carbon Observatory reveal a 16‐day shift in the seasonal cycle of photosynthesis relative to 2018, along with a 15% lower peak value. We estimate a reduction of 0.21 PgC in cropland gross primary productivity in June and July, partially compensated in August and September (+0.14 PgC). The extension of the 2019 growing season into late September is likely to have benefited from increased water availability and late‐season temperature. Ultimately, this change is predicted to reduce the crop productivity in the Midwest Corn/Soy belt by ~15% compared to 2018. Using an atmospheric transport model, we show that a decline of ~0.1 PgC in the net carbon uptake during June and July is consistent with observed CO2 enhancements of up to 10 ppm in the midday boundary layer from Atmospheric Carbon and Transport‐America aircraft and over 3 ppm in column‐averaged dry‐air mole fractions from Orbiting Carbon Observatory. This study quantifies the impact of floods on cropland productivity and demonstrates the potential of combining solar‐induced chlorophyll fluorescence with atmospheric CO2 observations to monitor regional carbon flux anomalies.

Since the proposal of the notion of nanodielectric, the space charge characteristics of nanodielectrics have been widely investigated. With the addition of nanoparticles, some nanodielectrics exhibit smaller space charge accumulation amount during the polarisation, and also faster charge decay during the depolarisation, which is believed to be related to the interfacial layer between the nanoparticle and the base material. In this study, the space charge measurement methods, theoretical models, and experimental results are reviewed in detail. Space charge measurement methods have been greatly improved after more than 20 years development. The nature of the interfacial layer between the nanoparticle and the base material has been investigated in detail, and based on that, several models are proposed to explain some electrical experimental results of nanodielectrics. Furthermore, the parameters of nanoparticle (such as the type, size, amount, shape, and the surface modification), the experimental conditions, and the base material properties can strongly affect the space charge characteristics of nanodielectrics. This study will provide useful research results and conclusions for researchers, and may also be an overview for recent study and an outlook for future investigation on space charge characteristics of nanodielectrics.