[Wetlands of priority restoration in Northeast China based on spatial analysis].

By using GIS/RS technology, and from the aspects of landscape structure, river- and road densities, wetness index, geomorphology, and cultivated land productivity, a spatial analysis was made on the potentiality of wetland restoration in Northeast China, with the regions of priority and secondary priority restoration wetlands determined. Then, by using the coordinated development index of crop production and wetland as well as the landscape indices, the wetland restoration effect was verified. In Northeast China, the wetland area of priority restoration was 1.78 x 10(6) hm2, among which, farmland and grassland were the main types for restoration, accounting for 96.7% of the total, and mainly located in the Sanjiang Plain in the northeastern part and the Songnen Plain in the central part of Northeast China. The wetland area of secondary priority restoration was 1.03 x 10(6) hm2. After the restoration of the wetlands, the wetland area in Northeast China would be increased by 37.4%, compared with the present wetland area, and the value of the coordinated development index of crop production and wetland would increase from 0.539 before restoration to 0.733 after restoration. The landscape pattern would be more benefit to the performance of the ecological functions of the wetlands. This study revealed that the restoration scheme of the wetlands in Northeast China based on spatial analysis was practicable, which could provide data support for the implement of wetland restoration and the improvement of ecological environment in Northeast China.

[Research on hyperspectral remote sensing in monitoring snow contamination concentration].

Contaminants in the snow can be used to reflect regional and global environmental pollution caused by human activities. However, so far, the research on space-time monitoring of snow contamination concentration for a wide range or areas difficult for human to reach is very scarce. In the present paper, based on the simulated atmospheric deposition experiments, the spectroscopy technique method was applied to analyze the effect of different contamination concentration on the snow reflectance spectra. Then an evaluation of snow contamination concentration (SCC) retrieval methods was conducted using characteristic index method (SDI), principal component analysis (PCA), BP neural network and RBF neural network method, and the estimate effects of four methods were compared. The results showed that the neural network model combined with hyperspectral remote sensing data could estimate the SCC well.

[Comparison of methods for estimating soybean chlorophyll content based on visual/near infrared reflection spectra].

The estimation of crop chlorophyll content could provide technical support for precision agriculture. Canopy spectral reflectance was simulated for different chlorophyll levels using radiative transfer models. Then with multiperiod measured hyperspectral data and corresponding chlorophyll content, after extracting six wavelet energy coefficients from the responded bands, an evaluation of soybean chlorophyll content retrieval methods was conducted using multiple linear regression, BP neural network, RBF neural network and PLS method. The estimate effects of the three methods were compared afterwards. The result showed that the three methods based on wavelet analysis have an ideal effect on the chlorophyll content estimation. R2 of validated model of multiple linear regression, BP neural network, RBF neural network and PLS method were 0. 634, 0. 715, 0. 873 and 0.776, respectively. PLS based on Gaussian kernel function and RBF NN methods were better with higher precision, which could estimate chlorophyll content stably.

[Light absorption by suspended particulate matter in Chagan Lake, Jilin].

Spectral characteristics and the magnitudes of light absorption by suspended particulate matter were determined by spectrophotometry in this optically complex Lake Chagan waters for the purpose of surveying the natural variability of the absorption coefficients to parameterize the bio-optical models for converting satellite or in-situ water reflectance signatures into water quality information. Experiments were carried out on seasonal frozen Lake Chagan, one representative inland case-2 water body in Northeast of China. Particulate absorption properties analyzed using the field data on July 15th and October 12th 2009 were measured using the quantitative filter technique to produce absorption spectra containing several fractions that could be attributed to two main optical active constituents (OACs) phytoplankton pigments and non-algal particulates (mineral sediments, and organic detritus). Results suggested that the suspended particulate matter (SPM) concentration was higher while phytoplankton biomass (chlorophyll-a concentration) was lower in July and that in October. The spectral shape of total suspended particulate matter resembled that of non-algal particulates which contributed greater than phytoplankton in total particulate absorption during both periods. An obvious absorption peak occurring at around 440 nm exhibited an increase in phytoplankton contribution in October. Non-algal particulate absorption at 440 nm (a(NAP) (440)) had better correlation with total suspended particulate matter concentration than that with chlorophyll-a over the two periods. Light absorption by phytoplankton pigments in the Chagan lake region was generally lower than that of non-algal components. Chl. a dominating phytoplankton pigment composition functioned exponentially with its absorption coefficients at 440 and 675 nm specifically, the average values of which in July were 0.146 8 m2 x mg(-1) and 0.050 3 respectively while in October they were 0.153 3 and 0.013 2 m2 x mg(-1) varying regionally and seasonally due to the changes in specific composition, light and nutrient conditions.

[Optimization effect of nitrogen and phosphorus removal in unifed SBR process for domestic wastewater].

Appropriate change of the traditional operation modes was investigated in a UniFed SBR lab-scale apparatus treating actual domestic wastewater with low C/N and C/P. Results showed that when the feed/decant time was extended from 2 h to 3 h and 4 h, the phosphorous removal efficiency increased from 59.93% to 88.45% without any external carbon source. In the mode of anoxic-aerobic condition, TIN of the effluent reduced obviously, the removal efficiency increased from 49.54% to 60.75% for utilizing limited substrate in influents with low C/N = 2.57, adequately. In the mode of alternation of anoxic-aerobic condition, the nitrogen and phosphorous removal efficiency increased clearly. The carbon source in the influent can be used adequately and it occurred denitrifying dephosphatation in anoxic segment 2. This mode was optimal for the treatment of actual domestic wastewater with low C/N and C/P.

[Effects of influent C/N ratio on performance of UniFed SBR process].

The effects of 7 groups of different influent C/N ratio (2.75, 4.28, 5.7, 6.5, 6.97, 8.08, 11.19) on the removal efficiencies of total nitrogen, phosphorus and COD as well as the sludge settling performance were investigated in a UniFed SBR lab-scale apparatus treating actual domestic wastewater. The results showed that when the C/N ratio was lower than 5.7, TN removal efficiency increased sharply as C/N ratio increased, from 43.6% of 2.75 to 80.84% of 5.7. Afterwards, TN removal efficiency increased very slowly as C/N ratio increased, because only TN removal efficiency caused by SND during aeration period could be enhanced. P removal efficiency increased as C/N ratio increased, because PAOs could get more organic carbon source from the influent to produce PHB and release PO4(3-), avoiding the adverse influence of NO(x)- on PO4(3-) release. The higher the C/N ratio, the more the quantities of P release and uptake, the quicker P uptake rate, the better P removal performance was. Regardless of the C/N ratio, excellent COD (average 93.15%) removal efficiencies were maintained throughout the experiment. When Influent C/N ratio was bigger than 6.97 and organic load exceeded 0.38 kg/(kg x d), SVI rose quickly as C/N ratio increased. Non-silk bacteria sludge bulge appeared because of low DO and high organic load.