ALBERT

Description: Due to the unique advantages of microwave detection, such as its low restriction from the atmosphere and its capability to obtain structural information about ground targets, synthetic aperture radar (SAR) is increasingly used in agricultural observations. However, while SAR data has shown great potential for large-scale crop mapping, there have been few studies on the use of SAR images for large-scale multispecies crop classification at present. In this paper, a large-scale crop mapping method using multi-temporal dual-polarization SAR data was proposed. To reduce multi-temporal SAR data redundancy, a multi-temporal images optimization method based on analysis of variance (ANOVA) and Jeffries–Matusita (J–M) distance was applied to the time series of images after preprocessing to select the optimal images. Facing the challenges from smallholder farming modes, which caused the complex crop planting patterns in the study area, U-Net, an improved fully convolutional network (FCN), was used to predict the different crop types. In addition, the batch normalization (BN) algorithm was introduced to the U-Net model to solve the problem of a large number of crops and unbalanced sample numbers, which had greatly improved the efficiency of network training. Finally, we conducted experiments using multi-temporal Sentinel-1 data from Fuyu City, Jilin Province, China in 2017, and we obtained crop mapping results with an overall accuracy of 85% as well as a Kappa coefficient of 0.82. Compared with the traditional machine learning methods (e.g., random forest (RF) and support vector machine (SVM)), the proposed method can still achieve better classification performance under the condition of a complex crop planting structure.

Description: Quickly and efficiently monitoring soil nutrient contents using remote sensing technology is of great significance for farmland soil productivity, food security and sustainable agricultural development. Current research has been conducted to estimate and map soil nutrient contents in large areas using hyper-spectral techniques, however, it is difficult to obtain accurate estimates. In order to improve the estimation accuracy of soil nutrient contents, we introduced a GA-BPNN method, which combined a back propagation neural network (BPNN) with the genetic algorithm optimization (GA). This study was conducted in Guangdong, China, based on soil nutrient contents and hyperspectral data. The prediction accuracies from a partial least squares regression (PLSR), BPNN and GA-BPNN were compared using field observations. The results showed that (1) Among three methods, the GA-BPNN provided the most accurate estimates of soil total nitrogen (TN), total phosphorus (TP) and total potassium (TK) contents; (2) Compared with the BPNN models, the GA-BPNN models significantly improved the estimation accuracies of the soil nutrient contents by decreasing the relative root mean square error (RRMSE) values by 15.9%, 5.6% and 20.2% at the sample point level, and 20.1%, 16.5% and 47.1% at the regional scale for TN, TP and TK, respectively. This indicated that by optimizing the parameters of BPNN, the GA-BPNN provided greater potential to improving the estimation; and (3) Soil TK content could be more accurately mapped by the GA-BPNN method using HuanJing-1A Hyperspectral Imager (HJ-1A HSI) (manufacturer: China Aerospace Science and Technology Corporation; Beijing, China) data with a RRMSE value of 20.37% than the soil TN and TP with the RRMSE values of 40.41% and 34.71%, respectively. This implied that the GA-BPNN model provided the potential to map the soil TK content for the large area. The research results provided an important reference for high-accuracy prediction of soil nutrient contents.

Description: Development of a sustainable process for designing and synthesising an active and stable catalyst for hydrochlorination of acetylene is challenging, yet crucial, for industrial vinyl chloride monomer (VCM) production. Herein, direct synthesis of bimetallic AuCu catalysts using organic aqua regia (OAR) preparation methods was investigated. In comparison with conventional aqua regia (AR), bimetallic AuCu catalysts synthesised from OAR exhibit enhanced activity and stability. After careful characterisation of the catalyst samples using X-ray diffraction patterns (XRD), Scanning transmission electron microscopy (STEM), X-ray photoelectron spectroscopy (XPS), and Temperature-programmed desorption (TPD), this observation was justified for the following reasons: 1) the existence of sulphur and nitrogen atoms stabilised the cationic Au active sites, and 2) OAR helped to sustain the function of the Cu promotor by stabilising it. Advanced understanding on the importance of promoter stability has unveiled new perspectives for this research area.

Description: The ecological status of the semi-arid steppes in China is fragile. Under the long-term and high-intensity development of mining, the ecological integrity and biodiversity of steppe landscapes have been destroyed, causing soil pollution, grassland degradation, landscape function defect, and so on. Previous studies have mainly focused on ecosystem health assessment in mining areas. Landscape ecological health (LEH) pays more attention to the interactions between different ecosystems. Therefore, the ecological assessment of mining cities is more suitable on a landscape scale. Meanwhile, the existing LEH assessment index systems are not applicable in ecologically fragile areas with sparse population, underdeveloped economy, and in relatively small research areas. The purpose of this study was to construct a LEH assessment index system and evaluate the LEH of a mining city located in a semi-arid steppe. Xilinhot is a typical semi-arid steppe mining city in China. The contradictions between the human, land and ecological environment are serious. A new model Condition, Vigor, Organization, Resilience, and Ecosystem (CVORE) model was constructed that integrated five subsystems (services) from the perspectives of ecology, landscape ecology, mining science, and geography. This study used the CVORE model to systematically evaluate the LEH in Xilinhot city in terms of five LEH levels, including very healthy, healthy, sub-healthy, unhealthy and morbid landscape. Research results show that the areas of the very healthy, healthy, sub-healthy, unhealthy and morbid landscapes are 13.23, 736.35, 184.5, 66.76 and 20.63 km2, respectively. The healthy landscapes area accounts for 72.08% and most grasslands are healthy. The sub-healthy landscapes are mainly located around areas with higher disturbances due to human activities. The morbid or unhealthy landscapes are concentrated in the mining areas. The proposed CVORE model can enrich the foundations for the quantitative assessment of Landscape Ecological Health of Mining Cities in Semi-arid Steppe (LEHMCSS). This study provided a new LEH assessment approach (CVORE model), which can support landscape ecological restoration, ecological environmental protection and urban planning of the semi-arid steppe mining cities.

Description: The Chinese honey locust tree Gleditsia sinensis Lam. (Fabaceae) is a precious ecological and economic tree species that has wide-ranging usage. However, knowledge regarding seedling cultivation (especially the use of arbuscular mycorrhizal fungi (AMF)) is scarce, which limits the developent of Gleditsia plantations. A pot experiment was carried out under greenhouse conditions to estimate the effects of three AMF strains (Funneliformis mosseae 1, Funneliformis mosseae 2, and Diversispora tortuosa) on the growth, photosynthetic rate, and nutrient content of G. sinensis seedlings. Results showed that the growth parameters (seedling height, basal diameter, dry biomass) of the seedlings were significantly increased by each of the three AMF strains, associated with high root colonization rates (greater than 75%). Chlorophyll concentrations and photosynthetic rates were also increased by AMF, and phosphorus (P), and potassium (K) content in the three organs (leaf, stem, and root), and nitrogen (N) content in the leaf and stem of arbuscular mycorrhizal (AM) seedlings were significantly higher than in non-AM seedlings. Mycorrhizal dependency of the AM seedlings was greater than 350%, and significantly correlated with the increased P and K content in all three organs and increased N content in the leaf and stem. Positive effects of F. mosseae on growth and the nutrient content of seedlings were higher than those of D. tortuosa, but no significant different effects on G. sinensis seedlings were observed between the two strains of F. mosseae. Hence, growth of G. sinensis seedlings was effectively enhanced by AMF, with F. mosseae being more suitable for the inoculation of G. sinensis seedlings. These results indicate that arbuscular mycorrhization is beneficial for the growth of young G. sinensis plants. Further research is needed to determine whether the effects can be reproduced in a forest situation.

Description: In recent years, nitrite pollution has become a subject of great concern for human lives, involving a number of fields, such as environment, food industry and biological process. However, the effective detection of nitrite is an instant demand as well as an unprecedented challenge. Here, a novel nitrite sensor was fabricated by electrochemical deposition of palladium and platinum (Pd-Pt) nanocomposites on porous gallium nitride (PGaN). The obtained Pd-Pt/PGaN sensor provides abundant electrocatalytic sites, endowing it with excellent performances for nitrite detection. The sensor also shows a low detection limit of 0.95 µM, superior linear ampere response and high sensitivity (150 µA/mM for 1 to 300 µM and 73 µA/mM for 300 to 3000 µM) for nitrite. In addition, the Pd-Pt/PGaN sensor was applied and evaluated in the determination of nitrite from the real environmental samples. The experimental results demonstrate that the sensor has good reproducibility and long-term stability. It provides a practical way for rapidly and effectively monitoring nitrite content in the practical application.

Description: Groundwater is the most important source of drinking water. Fluoride was found in high concentrations in the groundwater from deep wells of the water supply in the southern main Ethiopian rift. The high concentration of fluoride is dominantly geogenic rather than anthropogenic in origin, as the agricultural area was not found to be contaminated with NO3−. Knowledge of fluoride enrichment will help to provide management plans for developing deep groundwater and minimizing the health risks of exposure to fluoride. The chemical processes of fluoride were investigated in the waters in the Bilate River basin using hydrochemical and isotopic tools. The F− concentration ranged from 0.5 to 1.29 mg/L in water from shallow wells and from 0.48 to 5.61 mg/L in water from deep wells. Seventy percent of deep well samples had F− 〉 1.5 mg/L higher than the World Health Organization potable guideline. The high fluoride concentration in the groundwater was mainly situated in the rift valley of the Bilate River basin, in contrast with low F− groundwater in the highland. The concentration of fluoride was lowest in Ca-Mg-HCO3 type groundwater and highest in Na-HCO3 type groundwater. Moreover, F− was positively correlated with HCO3−, Na+, Na+/Ca2+ and pH in groundwater and Na+/Ca2+ ratios were increased along the flow path. Hydrogeological, hydrodynamic and hydrochemical conditions are responsible for fluoride accumulation in the deep aquifers. Strong dynamic flow in highland areas flush away weathered chemical components (e.g., F−). Thus, surficial weathering is not a major controlling factor for high concentrations of Fluoride in deep groundwater but the combination of silicate hydrolysis and ion exchange mainly control fluoride enrichment in stagnant flow environments.

Description: This paper proposes and demonstrates a phase-sensitive optical time domain reflectometry (Φ-OTDR) sensing system with multi-spatial resolution (MSR) analysis property. With both theoretical analysis and an experiment, the qualitative relationship between spatial resolution (SR), signal-to-noise ratio (SNR) and the length of the vibration region has been revealed, which indicates that choosing a suitable SR to analyze the vibration event can effectively enhance the SNR of a sensing system. The proposed MSR sensing scheme offers a promising solution for the performance optimization of Φ-OTDR sensing systems, which can restore vibration events of different disturbance range with optimum SNR in merely a single measurement while maintaining the same detectable frequency range.

Description: The determination of microscopic residual oil distribution is beneficial for exploiting reservoirs to their maximum potential. In order to investigate microscopic residual oil during the carbon dioxide (CO2) huff-and-puff process in tight oil reservoirs, several CO2 huff-and-puff tests with tight sandstone cores were conducted at various conditions. Then, nuclear magnetic resonance (NMR) was used to determine the microscopic residual oil distribution of the cores. The experiments showed that the oil recovery factor increased from 27.22% to 52.56% when injection pressure increased from 5 MPa to 13 MPa. The oil recovery was unable to be substantially enhanced as the injection pressure further increased beyond the minimum miscible pressure. The lower limit of pore distribution where the oil was recoverable corresponded to relaxation times of 2.68 ms, 1.29 ms, and 0.74 ms at an injection pressure of 5 MPa, 11 MPa, and 16 MPa, respectively. Longer soaking time also increased the lower limit of the oil-recoverable pore distribution. However, more cycles had no obvious effect on expanding the interval of oil-recoverable pore distribution. Therefore, higher injection pressure and longer soaking time convert the residual oil in smaller and blind pores into recoverable oil. This investigation provides some technical ideas for oilfields in design development programs for optimizing the production parameters during the CO2 huff-and-puff process.

Description: In this study, mangrove seedlings Kandelia obovata were firstly introduced to Zhoushan in Eastern China at 29° 93′ N from Xuwen in South China at 20° 34′ N in April 2016. In order to analyze ecophysiological differences of K. obovata seedlings domesticated in Zhoushan, the growth status and antioxidant system of K. obovata exposed to natural low temperature were studied through situ measurements. The results showed that K. obovata seedlings introduced artificially to Zhoushan grew slowly when subjected to natural cold stress. The chlorophyll contents exhibited a decreased tendency. In addition, 2-butanol and 2,3-butanediol were firstly found in K. obovata after being moved to Zhoushan, which are specific substances produced by K. obovata under low-temperature stress. Moreover, there was a synergistic competition mechanism in the antioxidant enzyme system in K. obovata, in which superoxide dismutase (SOD) would convert oxygen radicals to hydrogen peroxide, and then catalase (CAT) and peroxidase (POD) could work together to remove hydrogen peroxide. This study provides a foundation for better understanding of the response of mangroves to natural low temperature at high latitudes.