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Analysis of Sun photometer measured and satellite retrieved aerosol optical depth (AOD) data has shown that major aerosol pollution events with very high fine mode AOD (>1.0 in midvisible) in the China/Korea/Japan region are often observed to be associated with significant cloud cover. This makes remote sensing of these events difficult even for high temporal resolution Sun photometer measurements. Possible physical mechanisms for these events that have high AOD include a combination of aerosol humidification, cloud processing, and meteorological covariation with atmospheric stability and convergence. The new development of Aerosol Robotic Network Version 3 Level 2 AOD with improved cloud screening algorithms now allow for unprecedented ability to monitor these extreme fine mode pollution events. Further, the spectral deconvolution algorithm (SDA) applied to Level 1 data (L1; no cloud screening) provides an even more comprehensive assessment of fine mode AOD than L2 in current and previous data versions. Studying the 2012 winter‐summer period, comparisons of Aerosol Robotic Network L1 SDA daily average fine mode AOD data showed that Moderate Resolution Imaging Spectroradiometer satellite remote sensing of AOD often did not retrieve and/or identify some of the highest fine mode AOD events in this region. Also, compared to models that include data assimilation of satellite retrieved AOD, the L1 SDA fine mode AOD was significantly higher in magnitude, particularly for the highest AOD events that were often associated with significant cloudiness.

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Nitrogen contamination is one of the most serious problems in the Yellow River of China. This study was conducted to analyze monitoring data on nitrogen contamination for the Yellow River basin in the years 1980, 1990, 1997, and 1999. Several significant results have arisen from the study. First, in conjunction with an increase in economic indexes from the Yellow River's upper basin to its lower basin, the nitrogen concentration in the tributaries also showed an increasing trend from the upper to the lower basin, which, in turn, led to an increase in the nitrogen concentration of the mainstream from the upper to the lower reaches. Second, nitrogen in the river water in the mainstream and the tributaries of the Yellow River was attributed mainly to point sources. In spite of the fact that the ratio of point to nonpoint sources decreased from 2.7 in 1990 to 1.8 in 1997 for total inorganic nitrogen in river water at the Tongguan Station in the lower basin, point sources increased more than nonpoint sources. Third, the ammonium nitrogen and total inorganic nitrogen content of the river water increased significantly in the mainstream and the tributaries during the 1980-1999 period, a change caused by an increase in wastewater discharge and nitrogenous fertilizer application in the Yellow River catchment.

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Estimation for weather-related failure probability of overhead transmission lines is essential in the reliability assessment of a power system. This paper analyzes the outage and weather data of 110 kV overhead transmission lines in the Guangxi Zhuang Autonomous Region of China during 2011-2014. The result reveals obvious uneven distributions of outage events for time and space due to the spatial and temporal variation of severe weather. Based on the results, an estimation method is proposed in this paper. Split and aggregation is used to smooth the outage and weather data. The poisson model is adopted in our method to investigate the statistic characteristics of transmission line outage events. Regression analysis is applied to obtain the correlation between the weather intensity and history failure rate. Furthermore the method proposed is validated against the empirical outage data.