Based on the analysis of wind data measured at one wind measurement tower over Huangang Wind Farm in Jiangsu Province from Dec. 2010 to Nov. 2011, it was calculated that at 10, 50, 70 and 80 m heights the annual average wind speed was 4.0?6.1 m/s, the annual average wind power density was 80.4?238.4 W/m2, the annual effective wind power density was 116.5?262.5 W/m2, the annual effective hours were 5777?7845 h, and the annual effective wind energy density was 679.3?2041.5 (kW?h)/m2. In addition, the dominant wind directions were NNE, N and NE, the sum of them took up nearly 30% of the full year wind directions, the wind energy density of the dominant wind directions accounted for almost 50% of the full year wind energy density, and the wind speed was mainly ranging from 3 to 8 m/s, about 80% of the full year wind speeds. Overall, wind energy resource was abundant in this region. Especially the hub height of the already built wind turbines had the wind power density of more than 250 W/m2, and the effective hours took up nearly 90% of the full year. Therefore, wind energy resource had a great value of development and utilization in this region.

The aerosol optical depth (AOD) products from Moderate Resolution Imaging Spectroradiometer (MODIS), aerosol extinction coefficient profiles from Light Detection and Ranging (LIDAR), surface relative humidity data and particulate matter (PM) mass concentration data over Yuan Long, Hong Kong in 2008 were used in the remote sensing of surface suspended particulate matter mass distribution. LIDAR data were used to get the relationship among surface aerosol extinction coefficient, LIDAR AOD and aerosol scale height, which was further applied in the retrieval of the distribution of surface aerosol extinction coefficients with satellite AOD. After considering relative humidity effect, the correlation between satellite estimated aerosol extinction coefficients and the corresponding surface PM mass was investigated. Finally, the surface PM mass distribution was obtained by synergy usage of satellite and LIDAR measurements. The results show that the correlation coefficients between the estimated aerosol extinction coefficients and the surface PM mass are 0.57?0.86 for PM2.5 and 0.59?0.78 for PM10, respectively. The Root Mean Square Errors (RMSEs) between estimated PM and surface measured PM mass are 11.64?25.34 g/m³ for PM2.5 and 24.64?91.64 g/m³ for PM10. Satellite remote sensing provides a promising way in atmospheric suspended particulate matter monitoring. The 1-km resolution AOD product is more suitable for describing the pollution in the urban areas with complicated topography.

The MPL observation data in Beijing is used to develop two new algorithms which will not need to refer to the low SNR signal in high altitude. In the first algorithm, the boundary in mixing layer is chosen in the Fernald’s theory. Then the lidar constant can be retrieved by combining AOD. Compared with the data from the automatic meteorological station locates in the same place, this algorithm seems viable for lidar’s extinction coefficient retrieval. In the second algorithm, since the range corrected lidar data near the surface is linear relate to the surface extinction coefficient, the visibility data in the surface could be used to calculate the lidar constant. The result of the lidar constant and the average extinction-to-backscatter ratio during the experiment period are similar to the first algorithm. In these two algorithms, the lidar constant is retrieved without using the high altitude signal. In the end, the lidar observation of a classic aerosol case when a Siberian High passes through Beijing is analyzed. By comparing the lidar observation with the Nanjiao Observation Station data, the lidar retrieval and the new algorithm are considered to be reliable.