High-performance piezoelectric nanogenerators based on Cs₂Ag_0.3Na_0.7InCl₆ double perovskites with high polarity induced by Zr/Te codoping

Piezoelectric nanogenerators (PENGs), which operate based on mechanical-to-electrical energy conversion, have been widely explored for exciting applications in modern devices such as wearable electronics, self-powered sensors, and energy harvesters. Herein, we report on high-performance PENGs based on Cs2Ag0.3Na0.7InCl6 double perovskite (CDP) within a polyvinylidene fluoride (PVDF) matrix, which exhibit enhanced polarity due to rationally designed Zr/Te codoping. As a proof of concept, the resultant PENGs based on Zr/Te codoped CDP@PVDF deliver an excellent piezoelectric output, with a maximum open-circuit voltage and short-circuit current density of 67 V and 18 μA·cm−2. This level of performance is ∼19 and ∼12 times higher than PVDF-based PENGs with no CDP, and ∼2 and ∼4 times higher than CDP@PVDF-based PENGs without doping or with single Te doping, and ∼1 and ∼2 times higher than CDP@PVDF-based PENGs with single Zr doping, respectively. Moreover, the as-assembled PENGs exhibit impressive potential in wearable energy harvesters, motion sensors, and DC-power devices with robust stability, underscoring their bright future toward practical applications.</p

A Temperature and Emissivity Separation Algorithm for Landsat-8 Thermal Infrared Sensor Data

On-board the Landsat-8 satellite, the Thermal Infrared Sensor (TIRS), which has two adjacent thermal channels centered roughly at 10.9 and 12.0 μm, has a great benefit for the land surface temperature (LST) retrieval. The single-channel algorithm (SC) and split-window algorithm (SW) have been applied to retrieve the LST from TIRS data, which need the land surface emissivity (LSE) as prior knowledge. Due to the big challenge of determining the LSE, this study develops a temperature and emissivity separation algorithm which can simultaneously retrieve the LST and LSE. Based on the laboratory emissivity spectrum data, the minimum-maximum emissivity difference module (MMD module) for TIRS data is developed. Then, an emissivity log difference method (ELD method) is developed to maintain the emissivity spectrum shape in the iterative process, which is based on the modified Wien’s approximation. Simulation results show that the root-mean-square-errors (RMSEs) are below 0.7 K for the LST and below 0.015 for the LSE. Based on the SURFRAD ground measurements, further evaluation demonstrates that the average absolute error of the LST is about 1.7 K, which indicated that the algorithm is capable of retrieving the LST and LSE simultaneously from TIRS data with fairly good results

Restriction Analysis of Transport Policy for Bridges Using the Trajectory Data

Roads are becoming increasingly congested with continuous rise in the number of vehicles. Restriction policies are selected to alleviate congestion in many cities. However, conclusions regarding the substantial effects of restriction policies have not been fully demonstrated. This study primarily aims to demonstrate whether traffic restrictions can control the driving habits of people to alleviate traffic pressure. Furthermore, this study investigates the effect on the traffic on the premise of a normalized restriction policy. Data were collected by bayonet systems in Ningbo. Results showed that vehicles restricted by the restriction policy only accounted for approximately 13%. Most drivers bypass restricted roads to avoid restrictions. The method proposed can effectively amend the trajectory deviation caused by the inaccuracy from the bayonet. Based on the results, some suggestions about the policy of restrictions were discussed

Effect of Aromatic Petroleum Resin on Damping Properties of Polybutyl Methacrylate

The damping properties of polybutyl methacrylate (PBMA)/aromatic petroleum resin (C9) composite were investigated in this work. In particular, a trace of styrene (St) was introduced to copolymerize with PBMA to improve the compatibility between C9 and matrix. The structure of the copolymer, P(BMA-co-St), was characterized by FTIR and 1HNMR. The P(BMA-co-St)/C9 composites were tested by differencial scanning calorimetry (DSC), scanning electron microscopy (SEM) and dynamical mechanical analysis (DMA). DSC curves of all P(BMA-co-1wt%St)/C9 composites expressed only one glass transition temperature (Tg). SEM images showed that C9 had good compatibility with the matrix after St was introduced. DMA curves indicated that the addition of C9 had a positive effect on the damping properties of PBMA. The loss tangent (tan&delta;) peak moved to a higher temperature with the increment content of C9, and the effective damping temperature range increased significantly. The influence of aromatic resin C9 and aliphatic resin (C5) on PBMA damping performance was compared. It was further shown that C9 with benzene ring effectively improved the damping performance of PBMA

Soil Moisture Assimilation Improves Terrestrial Biosphere Model GPP Responses to Sub-Annual Drought at Continental Scale

Due to the substantial gross exchange fluxes with the atmosphere, the terrestrial carbon cycle plays a significant role in the global carbon budget. Drought commonly affects terrestrial carbon absorption negatively. Terrestrial biosphere models exhibit significant uncertainties in capturing the carbon flux response to drought, which have an impact on estimates of the global carbon budget. Through plant physiological processes, soil moisture tightly regulates the carbon cycle in the environment. Therefore, accurate observations of soil moisture may enhance the modeling of carbon fluxes in a model–data fusion framework. We employ the Carbon Cycle Data Assimilation System (CCDAS) to assimilate 36-year satellite-derived surface soil moisture observations in combination with flask samples of atmospheric CO2 concentrations. We find that, compared to the default model, the performance of optimized net ecosystem productivity (NEP) and gross primary productivity (GPP) has increased with the RMSEs reduced by 1.62 gC/m2/month and 10.84 gC/m2/month, which indicates the added value of the ESA-CCI soil moisture observations as a constraint on the terrestrial carbon cycle. Additionally, the combination of soil moisture and CO2 concentration in this study improves the representation of inter-annual variability of terrestrial carbon fluxes as well as the atmospheric CO2 growth rate. We thereby investigate the ability of the optimized GPP in responding to drought by comparing continentally aggregated GPP with the drought index. The assimilation of surface soil moisture has been shown to efficiently capture the influences of the sub-annual (≤9 months drought durations) and large-scale (e.g., regional to continental scales) droughts on GPP. This study highlights the significant potential of satellite soil moisture for constraining inter-annual models of the terrestrial biosphere’s carbon cycle and for illustrating how GPP responds to drought at a continental scale

Soil Moisture Assimilation Improves Terrestrial Biosphere Model GPP Responses to Sub-Annual Drought at Continental Scale

Due to the substantial gross exchange fluxes with the atmosphere, the terrestrial carbon cycle plays a significant role in the global carbon budget. Drought commonly affects terrestrial carbon absorption negatively. Terrestrial biosphere models exhibit significant uncertainties in capturing the carbon flux response to drought, which have an impact on estimates of the global carbon budget. Through plant physiological processes, soil moisture tightly regulates the carbon cycle in the environment. Therefore, accurate observations of soil moisture may enhance the modeling of carbon fluxes in a model&ndash;data fusion framework. We employ the Carbon Cycle Data Assimilation System (CCDAS) to assimilate 36-year satellite-derived surface soil moisture observations in combination with flask samples of atmospheric CO2 concentrations. We find that, compared to the default model, the performance of optimized net ecosystem productivity (NEP) and gross primary productivity (GPP) has increased with the RMSEs reduced by 1.62 gC/m2/month and 10.84 gC/m2/month, which indicates the added value of the ESA-CCI soil moisture observations as a constraint on the terrestrial carbon cycle. Additionally, the combination of soil moisture and CO2 concentration in this study improves the representation of inter-annual variability of terrestrial carbon fluxes as well as the atmospheric CO2 growth rate. We thereby investigate the ability of the optimized GPP in responding to drought by comparing continentally aggregated GPP with the drought index. The assimilation of surface soil moisture has been shown to efficiently capture the influences of the sub-annual (&le;9 months drought durations) and large-scale (e.g., regional to continental scales) droughts on GPP. This study highlights the significant potential of satellite soil moisture for constraining inter-annual models of the terrestrial biosphere&rsquo;s carbon cycle and for illustrating how GPP responds to drought at a continental scale

China's Terrestrial Carbon Sink Over 2010–2015 Constrained by Satellite Observations of Atmospheric CO2 and Land Surface Variables

The magnitude and distribution of China's terrestrial carbon sink remain uncertain due to insufficient constraints at large scales, whereby satellite data offer great potential for reducing the uncertainty. Here, we present two carbon sink estimates for China constrained either by satellite CO2 column concentrations (XCO2) within the Global Carbon Assimilation System or by remotely sensed soil moisture and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) in addition to in situ CO2 observations within the Carbon Cycle Data Assimilation System. They point to a moderate size of carbon sinks of 0.34 ± 0.14 (mean ± unc.) and 0.43 ± 0.09 PgC/yr during 2010–2015, which are supported by an inventory-based estimate for forest and soil carbon sink (0.26 PgC/yr) and fall in the range of contemporary ensemble atmospheric inversions (0.25–0.48 PgC/yr). They also agree reasonably well on interannual variations, which reflect the carbon sink anomalies induced by regional droughts in southwest China. Furthermore, their spatial distributions are broadly consistent that of the forest inventory-based estimate, indicating that the largest carbon sinks locate in central and eastern China. Their estimates for forest carbon sink coincide fairly well with the inventory-based estimate across different regions, especially when aggregated to the north and south of China. Although enhanced recently by afforestation, China's carbon sink was also significantly weakened by regional droughts, which were often not fully represented in previous in situ CO2-based inversions due to insufficient observations. Our results suggest that satellite-based atmospheric CO2 and land surface observations are vital in characterizing terrestrial net carbon fluxes at regional scales

Recent global decline of CO2 fertilization effects on vegetation photosynthesis

The enhanced vegetation productivity driven by increased concentrations of carbon dioxide (CO2) [i.e., the CO2 fertilization effect (CFE)] sustains an important negative feedback on climate warming, but the temporal dynamics of CFE remain unclear. Using multiple long-term satellite- and ground-based datasets, we showed that global CFE has declined across most terrestrial regions of the globe from 1982 to 2015, correlating well with changing nutrient concentrations and availability of soil water. Current carbon cycle models also demonstrate a declining CFE trend, albeit one substantially weaker than that from the global observations. This declining trend in the forcing of terrestrial carbon sinks by increasing amounts of atmospheric CO2 implies a weakening negative feedback on the climatic system and increased societal dependence on future strategies to mitigate climate warming