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  • 1
    Publication Date: 2013-12-21
    Description: This study compared three broadband emissivity (BBE) datasets from satellite observations. The first is a new global land surface BBE dataset known as the Global Land Surface Satellite (GLASS) BBE. The other two are the North American ASTER Land Surface Emissivity Database (NAALSED) BBE and University of Wisconsin Global Infrared Land Surface Emissivity Database (UWIREMIS) BBE, which were derived from two independent narrowband emissivity products. Firstly, NAALSED BBE was taken as the reference to evaluate the GLASS BBE and UWIREMIS BBE. The GLASS BBE was more close to NAALSED BBE with a bias and root mean square error (RMSE) of −0.001 and 0.007 for the summer season, −0.001 and 0.008 for the winter season, respectively. Then, the spatial distribution and seasonal pattern of global GLASS BBE and UWIREMIS BBE for six dominant land cover types were compared. The BBE difference between vegetated areas and non-vegetated areas can be easily seen from two BBEs. The seasonal variation of GLASS BBE was more reasonable than that of UWIREMIS BBE. Finally, the time series were calculated from GLASS BBE and UWIREMIS BBE using the data from 2003 through 2010. The periodic variations of GLASS BBE were stronger than those of UWIREMIS BBE. The long time series high quality GLASS BBE can be incorporated in land surface models for improving their simulation results.
    Electronic ISSN: 2072-4292
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Published by MDPI Publishing
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  • 2
    Publication Date: 2014-08-26
    Description: We have investigated newly reported pneumoconiosis cases in the province of Hubei, China from 2008 to 2013, to identify the major problems and challenges, and explore possible solutions for its prevention and control. We analyzed the data on new cases of pneumoconiosis from annual reports, including case distributions, patient ages, exposure duration, disease stages, and enterprise types. A total of 3665 new pneumoconiosis cases were reported between 2008 and 2013 in Hubei Province. Coal workers’ pneumoconiosis and silicosis, which accounted for 97.19% of the total, were the most common types. The duration of exposure of 33.32% cases was less than 10 years. Most of the new pneumoconiosis cases worked in industries that produced coal, nonferrous metal, or building materials. About 42.46% of pneumoconiosis cases were from small and medium-sized enterprises. The proportion of cases with combined pneumoconiosis and tuberculosis was 6.6%, and the incidence of tuberculosis was highest in workers with silicosis. The current situation of pneumoconiosis in China is serious. Lack of attention to occupational health, inefficient surveillance, and weak occupational health services may have contributed to the increased new pneumoconiosis cases.
    Print ISSN: 1661-7827
    Electronic ISSN: 1660-4601
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Medicine
    Published by MDPI Publishing
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  • 3
    Publication Date: 2015-09-03
    Description: A phase-sensitive optical time domain reflectometer (Φ-OTDR) can be used for pipeline security. However, the sensing distance (less than 20 km) of traditional Φ-OTDR is too short for the needs of typical oil and gas pipeline monitoring applications (30–50 km). A simple structure Φ-OTDR system utilizing long pulse, balanced amplified detector and heterodyne detection is proposed in this paper and the sensing range is thereby increased to 60 km. Through analyzing the sensing principle of Φ-OTDR, a novel locating strategy is proposed to maintain the locating accuracy at a few meters when a long pulse (5 µs) is used. The increased pulse width deteriorates the time series of each sensing point seriously. In order to eliminate the deterioration, a data processing technique combining wavelet and empirical mode decomposition is applied in this system. The experiment results show that the sensing distance can be increased to 60 km and the locating accuracy is maintained at 6.8 m.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
    Published by MDPI Publishing
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