Fogs and hazes broke out many times in winter and spring of 2015～2016 in Baotou, China. It is not only very seriously influential on visibility, but also seriously harmful for human health. Based on this, data of 8 monitoring stations recording characteristics of particulate matters (PM) were analyzed to determine the characteristics of temporal and spatial pollution variation of PM2.5 and PM10 in the central urban districts of Baotou. According to the different functions of monitoring region, 5 districts were divided and the data of each district were screened and sorted. Winter and spring regional PM mass concentration order from high to low were obtained as follows: industrial area>commercial area>cultural area>transportation hub area>park sight spot. The monthly changing characteristics of particles about each district were obtained, and then the cause of formation was analyzed and summarized. Monthly variation curve of PM2.5 and PM10 mass concentration showed single valley in double peak pattern: the maximum was in December and the minimum was in February; daily variation indicated a good correlation between PM2.5 and PM10, both of which were significantly influenced by meteorological conditions; diurnal variation curve showed adouble peak-valley type. Meteorological factors such as daily average temperature, atmospheric pressure, relative humidity, precipitation were chosen and their individual relationships with concentrations of PM2.5 and PM10 were investigated using Spearman rank correlation analyses. It was demonstrated that the concentrations of PM2.5 and PM10 were positively correlated with temperature and atmospheric pressure, respectively, and strongly negatively correlated with wind speed and relative humidity. Wind speed, atmospheric pressure (with raining and snowing) and relative humidity were three key factors affecting the distributions of PM2.5 and PM10 concentration.

Ammonia is one of the main odors. A mid-infrared laser based gas sensor was developed for continuous monitoring of the ammonia in pollution emissions in the industrial environment. Different from the traditionalnear-infrared ammonia sensor, a mid-infrared distributed feedback inter-band cascade laser (DFB-ICL) was used as light source, tuned at the center of 3 μm, which could qualify the sensor to avoid from the interference of water vapor as well as carbon dioxide. A hollow silica waveguide was used for gas cell, and the core diameter is 1 mm, the length is 5 m. A home-made multi-channel digital lock-in amplifier was adopted to demodulate 1f/2f harmonics simultaneously so as to realize calibration-free measurement. Concentration gradient results show that this sensor has a linearity as high as 0.99917 as well as an uncertainty of 0.9%. Based on the Allan variance method, it can be clearly seen that the sensor shows a quite excellent stability performance with a detection limit as low as 9.7 ppb at the optimum integration time of 167 s.

SF6 in gas insulation systems may breakdown under high voltage, which can cause electrical system failure. An on-line gas detection and analysis system was developed for SF6 quality monitoring in gas insulation equipment. The basic components were introduced from the aspects of function modules, software/hardware development, as well as the final system integration. In order to validate the system feasibility, both laboratory and field tests were performed. Test results suggested that the system can improve the detection efficiency, and can make working environment safer for testers, which was important for the safety of electrical equipment.

Fine spectral information of hyper-spectral remote sensing provides a good prospect for parameters of water color inversion by remote sensing. However, for high spectral resolution and low spatial resolution, the current hyper-spectral remote sensing inversion models and algorithms of water color are generally lack of effective use of spatial information, so it is difficult to ensure accuracy and stability of the model. Taking Chaohu Lake, Anhui, China, as the study area, based on the space eight neighborhoods and genetic algorithm, hyper-spectral remote sensing HSI data of HJ-1A satellite is combined with the measured sample data to construct a hyper-spectral remote sensing inversion model of chlorophyll by the in-depth analysis of the spectral characteristics of water body. Based on matlab7.0 platform, the parameters of inversion model is calculated by the combined spectral indices and genetic algorithm. Under the spatial neighborhood analysis and genetic iteration, the concentration of chlorophyll is solved. The results show that the genetic algorithm abandons the traditional search methods, optimizes and searches water color space randomly using simulated evolution in the vicinity of the spatial domain by spectral information, jumps out of the local extreme point, can effectively improve the accuracy of model inversion.

Automatic aerosol observation network (AERONET) and FY-3A Moderate Resolution Imaging Spectrometer (FY-3A/MERSI) are matched by utilizing the method of band interpolation and temporal-spatial matching. The inversion precision of FY-3A/MERSI AOD products in Beijing, China and adjacent regions is verified and analyzed by using AERONET AOD data. The results show: (1) FY-3A AOD data presents a high relativity (R=0.733) with AERONET AOD data and generally less than it (bias=－0.012). (2) The higher the underlying surface vegetation coverage is, the higher the FY-3A AOD data retrieving accuracy is, and the accuracy in winter-spring season is higher than that in summer-autumn season. Also, the retrieval precision is greater in low aerosol concentration condition. The above conclusions can provide reference for the application of FY-3A/MERSI aerosol products in northern China.

Earth surface albedo is widely used in atmospheric radiation transmission and remote sensing imaging research. It plays an important role in the energy balance of the Earth’s atmospheric system, which reflects the reflection capacity of solar radiation on the surface. MODIS remote sensing data is used as the data source, and C++ language is used to design and develop the software. The design of the software includes the data source (MCD43B3) preprocessing, MySQL database design, pixel latitude and longitude coordinates acquisition, data storage and latitude and longitude parameter query surface albedo process. The surface albedo database of the China mainland is established, and the albedo data of a specific geographical location can be easily and quickly searched according to the latitude and longitude parameters.

Out-of-band response (out-of-band light leakage) is a significant factor affecting the radiometric calibration uncertainty of multispectral remote sensor (MsRS). For the MsRs out-of-band response measurement, correction and precision verification, the 443 nm band in multispectral imager using the functions of a novel spectrum-tunable integrating spheres reference light source (STIS) (i.e. discrete waveband and continuous spectrum output functions) was taken for example in batch experiments. After carrying out the out-of-band response measurement, correction and precision verification of multispectral imager, the weighted radiant luminance was amended based on the out-of-band response correction model, and compared with the measuring reference of spectral radiance meter. The results show that the difference between in-band weighted radiant luminance and measuring reference before and after the out-of-band response correction decreases from 8.8% to 2.9%, which confirms the application feasibility of STIS on the MsRS out-of-band response correction.

Cloud is a large obstacle to remote sensing image processing and analysis. In order to solve this problem, an optimizational cloud detection algorithm is proposed for GF-1 satellite image based on the spectral and textural information. In the cloud-like areas detected by spectral analysis, a new sub-image segment method and dynamic threshold is used to improve the accuracy of texture detection. The Otsu algorithm is used to restore the thick cloud boundary information, since neither the fixed spectral threshold setting nor textural detection can get the boundaries of cloud in a complex environment. The results show that this method can effectively detect the cloud cover in the remote sensing image, optimally extract thick cloud boundary information, and effectively separate thin cloud and thick cloud.