Abstract
Quantifying the drivers of terrestrial vegetation dynamics is critical for monitoring ecosystem carbon sequestration and bioenergy production. Large scale vegetation dynamics can be observed ...using the leaf area index (LAI) derived from satellite data as a measure of ‘greenness’. Previous studies have quantified the effects of climate change and carbon dioxide (CO
2
) fertilization on vegetation greenness. In contrast, the specific roles of land-use-related drivers (LURDs) on vegetation greenness have not been characterized. Here, we combined the Interior-Point Method-optimized ecosystem model and the Bayesian model averaging statistical method to disentangle the roles of LURDs on vegetation greenness in China from 2000 to 2014. Results showed a significant increase in growing season LAI (greening) over 35% of the land area of China, whereas less than 6% of it exhibited a significantly decreasing trend (browning). The overall impact of LURDs on vegetation greenness over the whole country was comparatively low. However, the local effects of LURDs on the greenness trends of some specified areas were considerable due to afforestation and urbanization. Southern Coastal China had the greatest area fractions (35.82% of its corresponding area) of the LURDs effects on greening, following by Southwest China. It was because of these economic regions with great afforestation programs. Afforestation effects could explain 27% of the observed greening trends in the forest area. In contrast, the browning impact caused by urbanization was approximately three times of the greening effects of both climate change and CO
2
fertilization on the urban area. And they made the urban area had a 50% decrease in LAI. The effects of residual LURDs only accounted for less than 8% of the corresponding observed greenness changes. Such divergent roles would be valuable for understanding changes in local ecosystem functions and services under global environmental changes.
Device-free localization (DFL) based on wireless sensor networks (WSNs) is expected to detect and locate a person without the need for any wireless devices. Radio tomographic imaging (RTI) has ...attracted wide attention from researchers as an emerging important technology in WSNs. However, there is much room for improvement in localization estimation accuracy. In this paper, we propose a geometry-based elliptical model and adopt the orthogonal matching pursuit (OMP) algorithm. The new elliptical model uses not only line-of-sight information, but also non-line-of-sight information, which divides one ellipse into several areas with different weights. Meanwhile the OMP, which can eliminate extra bright spots in image reconstruction, is used to derive an image estimator. The experimental results demonstrate that the proposed algorithm could improve the accuracy of positioning by up to 23.8% for one person and 33.3% for two persons over some state-of-the-art RTI methods.
Given the advantages of remote sensing, an increasing number of satellite aerosol optical depths (AOD) have been utilized to evaluate near-ground PM2.5. However, the spatiotemporal relationship ...between AODs and PM2.5 still lacks a comprehensive investigation, especially in some regions with severe pollution within China. Here, we investigated the spatiotemporal relationships between several satellite AODs and the near-surface PM2.5 concentration across China and its 14 representative regions during 2016–2018 using the correlation coefficient (R), the PM2.5/AOD ratio (η), the geo-detector (q), and the different aerosol-dominated regimes. The results showed that the MODIS AOD from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm strongly correlates with PM2.5 (R > 0.6) in China, particularly in the Chengyu (CY), Beijing-Tianjin-Hebei (BTH), and Yangtze River Delta (YRD) regions. The close correlations (R = 0.7) exist between PM2.5 and MODIS and VIIRS AOD from the deep blue (DB) algorithm in the CY, BTH, and YRD regions. Under the key aerosols affecting China (e.g., sulfate and dust), there is a strong correlation (R > 0.5) between the PM2.5 and MODIS and VIIRS AODs from the MAIAC and DB algorithms, with the higher concentration of ground-level PM2.5 per unit of these AODs (η > 130). The MAIAC AOD (Terra/Aqua) can better explain the spatial distribution (q > 0.4) of PM2.5 than those of AODs from the dark target (DT) and DB algorithms applied to the MODIS over China and its specific regions across seasons. The performance of the Advanced Himawari Imager (AHI) AOD (R > 0.5, q > 0.3) was close to that of the MAIAC AOD during the spring and summer; however, it was far less than the MAIAC AOD in the autumn and winter seasons. The investigation provides instructions for estimating the near-surface PM2.5 concentration based on AOD in different regions of China.
Device-free localization (DFL), which can detect and locate a person by measuring the changes in received signals, is one of the primary techniques in wireless sensor networks. Recently, research on ...fingerprint-based localization in changing environments has been receiving increasing attention. However, when the environment changes due to furniture or other objects are moved, there is still much room for localization accuracy improvement in fingerprint-based DFL. In this paper, we propose a novel DFL algorithm for changing environments: this algorithm features an enhanced channel-selection method and adopts the logistic regression classifier to improve the localization accuracy. The proposed frequency channel-selection method selects two correlated channels with higher Pearson correlation coefficient both in the training and testing procedures, which would be more robust to the environmental change. Meanwhile, the logistic regression classifier could counteract the negative influence on the localization accuracy, without the need for rebuilding the database in fingerprint-based DFL. Experimental results demonstrate that the logistic regression classifier has the lowest error rate among three related methods (k-nearest neighbours classifier, linear discriminant analysis classifier, and random forests classifier). In addition, the localization accuracy has been further improved by the proposed DFL algorithm than by the other state-of-the-art fingerprint-based methods.
Recently, a comment paper on "A New Elliptical Model for Device-Free Localization" (Sensors 2016, 16, 577) has been presented, and the authors have provided a modified model. However, there are still ...some misunderstandings. In this reply, we further explain the proposed elliptical model in (Sensors 2016, 16, 577) to make it more understandable.
Himawari-8 aerosol products have been widely used to estimate the near-surface hourly PM2.5 concentrations due to the high temporal resolution. However, most studies focus on the evaluation model. As ...the foundation of the estimation, the relationship between near-surface PM2.5 and columnar aerosol optical depth (AOD) has not been comprehensively investigated. In this study, we investigate the relationship between PM2.5 and advanced Himawari imager (AHI) AOD for 2016–2018 across mainland China on different spatial and temporal scales and the factors affecting the association. We calculated the Pearson correlation coefficients and the PM2.5/AOD ratio as the analysis indicators in 345 cities and 14 urban agglomerations based on the collocations of PM2.5 and AHI AOD. From 9:00 to 17:00 local time, the PM2.5-AOD correlation become significantly stronger while The PM2.5/AOD ratio markedly decrease in Beijing-Tianjin-Hebei, Yangtze River Delta, and Chengyu regions. The strongest correlation is between 12:00 and 14:00 LT (at noon) and between 13:00 and 17:00 LT (afternoon), respectively. The ratio in a day shows an obvious unimodal mode, and the peak occurred at around 10:00 or 11:00 LT, especially in autumn and winter. There is a pronounced variation of the PM2.5-AOD relationship in a week during the winter. Moreover, there are the strongest correlation and the largest ratio for most urban agglomerations during the winter. We also find that PM2.5 and AOD are not always correlated under different meteorological conditions and precursor concentrations. Furthermore, for the scattering-dominated fine-mode aerosol, there is a high correlation and a low ratio between PM2.5 and AOD. The correlation between PM2.5 and AHI AOD significantly increases with increasing the number of AOD retrievals on a day. The findings will provide meaningful information and important implications for satellite retrieval of hourly PM2.5 concentration and its exposure estimation in China, especially in some urban agglomerations.
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•The correlation between PM2.5 and AHI AOD is the strongest in the afternoon.•The PM2.5/AOD ratio is the largest at 10:00 local time during winter and autumn.•The PM2.5-AOD relationship varies pronounced in the week of winter.•The seasonal variation between PM2.5 and AOD exists large spatial heterogeneity.•The number of AHI AOD retrievals in a day affect the association with PM2.5.
•The ceramic absorbers with vertical pores were fabricated by freeze casting.•The evaporation properties of selective and non-selective absorbers were compared.•The ceramic absorber shows excellent ...cycle stability and desalination ability.
Solar-driven interfacial evaporation is a green and potential method to alleviate the water resource crisis. However, high energy utilization efficiency and long-term stability are the two challenges faced by absorbers. Herein, to change the situation, selective ceramic absorbers with continuous vertical pore structure were fabricated by a freeze casting technology for efficient solar evaporation. The perovskite oxide Sm0.5Sr0.5CoO3-δ (selective) and La0.5Sr0.5Co0.5Ni0.5O3-δ (nonselective) ceramics were chose to fabricate the absorbers. The comparison of the porous absorbers prepared by Sm0.5Sr0.5CoO3-δ and La0.5Sr0.5Co0.5Ni0.5O3-δ indicated that the selective absorber revealed better evaporation performance (1.22 kg m−2h−1) than that of the nonselective absorber (1.12 kg m−2h−1). The highest evaporation rate (1.27 kg m−2h−1) was observed on the Sm0.5Sr0.5CoO3-δ absorber with 60 wt% solid content and −70 ℃ freezing temperature through the optimization of process parameters. Meanwhile, the selective ceramic absorbers showed excellent cycle stability and desalination quality. This work demonstrates the advantage of selective absorption materials and expands the application of ceramic absorbers in solar-driven interfacial evaporation.
Process-based ecosystem models are increasingly used to simulate the effects of a changing environment on vegetation growth in the past, present, and future. To improve the simulation, the multimodel ...ensemble mean (MME) and ensemble Bayesian model averaging (EBMA) methods are often used in optimizing the integration of ecosystem model ensemble. These two methods were compared with four other optimization techniques, including genetic algorithm (GA), particle swarm optimization (PSO), cuckoo search (CS), and interior-point method (IPM), to evaluate their efficiency in this article. Here, we focused on eight commonly used ecosystem models to simulate vegetation growth, represented by the growing season leaf area index (LAIgs), collected globally from 2000 to 2014. The performances of the multimodel ensembles and individual models were compared using the satellite-observed LAI products as the reference. Generally, ensemble simulations provide more accurate estimates than individual models. There were significant performance differences among the six tested methods. The IPM ensemble model simulated LAIgs more accurately than the other tested models, as the reduction in the root-mean-square error was 84.99% higher than the MME results and 61.50% higher than the EBMA results. Thus, IPM optimization can reproduce LAIgs trends accurately for 91.62% of the global vegetated area, which is double the area of the results from MME. Furthermore, the contributions and uncertainties of the individual models in the final simulated IPM LAIgs changes indicated that the best individual model (CABLE) showed the greatest area fraction for the maximum IPM weight (32.49%), especially in the low-lalitude to midlatitude areas.
Himawari-8 aerosol products have been widely used to estimate the near-surface hourly PM
concentrations due to the high temporal resolution. However, most studies focus on the evaluation model. As ...the foundation of the estimation, the relationship between near-surface PM
and columnar aerosol optical depth (AOD) has not been comprehensively investigated. In this study, we investigate the relationship between PM
and advanced Himawari imager (AHI) AOD for 2016-2018 across mainland China on different spatial and temporal scales and the factors affecting the association. We calculated the Pearson correlation coefficients and the PM
/AOD ratio as the analysis indicators in 345 cities and 14 urban agglomerations based on the collocations of PM
and AHI AOD. From 9:00 to 17:00 local time, the PM
-AOD correlation become significantly stronger while The PM
/AOD ratio markedly decrease in Beijing-Tianjin-Hebei, Yangtze River Delta, and Chengyu regions. The strongest correlation is between 12:00 and 14:00 LT (at noon) and between 13:00 and 17:00 LT (afternoon), respectively. The ratio in a day shows an obvious unimodal mode, and the peak occurred at around 10:00 or 11:00 LT, especially in autumn and winter. There is a pronounced variation of the PM
-AOD relationship in a week during the winter. Moreover, there are the strongest correlation and the largest ratio for most urban agglomerations during the winter. We also find that PM
and AOD are not always correlated under different meteorological conditions and precursor concentrations. Furthermore, for the scattering-dominated fine-mode aerosol, there is a high correlation and a low ratio between PM
and AOD. The correlation between PM
and AHI AOD significantly increases with increasing the number of AOD retrievals on a day. The findings will provide meaningful information and important implications for satellite retrieval of hourly PM
concentration and its exposure estimation in China, especially in some urban agglomerations.
Advanced Himawari Imager (AHI) aboard Himawari-8 provides hourly Aerosol Optical Thickness (AOT) products, widely used to assimilation models and ground-level particulate matter (PM) concentration ...retrievals. However, the performance of AHI AOT products remains unclear under different air quality conditions. In this study, we evaluate the performance of the AHI hourly AOT products with ground-based AOT observations from four Aerosol Robotic NETwork (AERONET) sites for 2018 over Beijing under different pollution levels and aerosol types. Near-surface PM concentrations are used to categorize air quality as clean, moderate, and heavy pollution, and the aerosol types (biomass burning and urban/industrial (BMA_UIA), maritime (MA), dust (DA), mixed-type (MIXA)) are classified based on the threshold limits of AERONET aerosol properties. Overall, the AHI hourly AOT achieves good consistency with AERONET measurements in Beijing (correlation coefficient (R) = 0.78 and a root-mean-square-error (RMSE) = 0.29). Under clean conditions, the AOT successful retrieval rate is more than 80%, while it is deficient for moderate and heavy pollution. AOT for clean and moderate pollution performs better than that for heavy pollution. Moreover, AHI AOT retrievals for fine mode aerosol (BMA_UIA) are in good agreement with AERONET observations, and the performance is better than that under coarse mode aerosol (MA and DA) conditions. AHI AOT may capture the spatiotemporal distribution of fine particles pollution over Beijing. These findings will provide useful information for the improvement of the aerosol model of the retrieval algorithm and the monitoring of urban fine particles pollution.
•Under clean conditions, the AOT successful retrieval rate is more than 80%.•AHI AOT retrievals for fine mode aerosol are better than that under coarse mode aerosol conditions.•AHI AOT may capture the spatiotemporal distribution of fine particles pollution over Beijing.
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