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Ma G.,Beijing Normal University | Ma G.,Chinese Research Academy of Environmental Sciences | Wang Y.,Beijing Normal University | Wang Y.,China National Environmental Monitoring Center | And 7 more authors.
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | Year: 2011

In order to study the diversity characteristic and pollution load of non-point source pollution of nitrogen and phosphorus in the Songhua River, and provide a reference for the water environment management, based on remote sensing (RS) and geographic information system (GIS) technique, using the data of digital elevation model (DEM), county statistics and land use in Songhua River Basin in 2008, the space simulation and load estimation of non-point source pollution in the Songhua River Basin was conducted by export coefficient model (ECM), and the diversity of the non-point source pollution characteristics in the basin was analyzed. The results showed that the non-point source total nitrogen (TN) load was 112.99×10 4 t and total phosphorus (TP) load was 4.05×10 4 t in the Songhua River Basin in 2008 respectively. Nenjiang River sub-basin was the maximum load of TN and TP which was 52.80×10 4 t and 1.79×10 4t respectively, accounting for 46.09% and 44.14% of the total TN and TP. The maximum load intensity of TN and TP was the second Songhua River sub-basin which was 2.96 t/(km 2·a) and 0.11 t/(km 2·a) respectively. From the perspective of non-point sources, 95.92×10 4t of TN loads and 3.40×10 4t of TP loads were caused by anthropogenic activities, accounting for 83.90% and 83.94% of the total TN and TP respectively. Anthropogenic factor is the key of non-point source TN and TP of the Songhua River, natural causes should not be ignored as well. The results can provide reference for water environment management and overall understanding the non-point source pollution of the Songhua River.


Dong W.,Chinese Research Academy of Environmental Sciences | Dong W.,State Environment Protection Key Laboratory of Regional Eco process and Function Assessment | Shu J.,Chinese Research Academy of Environmental Sciences | Shu J.,State Environment Protection Key Laboratory of Regional Eco process and Function Assessment | And 4 more authors.
Advanced Materials Research | Year: 2012

The lake carbon circle is an important part of regional carbon circle research. The lake ecosystem is the important carbon storeroom in the earth, it absorbs a mass of carbon dioxide through photosynthesis, and transforms carbon dioxide to organically carbon, and then the lake has traits of abundant carbon reserves and heavy carbon density. As the especial geographical place and upper productivity, the lake has significant role in carbon circle. By now, there is clear acquaintanceship of greenhouse effect problem, especial we have qualitative and quantificational understanding of ocean carbon circle primary. But we have a little research of lake carbon circle and carbon flux. There are many lakes in China, so it is crucial meaning to study lake carbon circle. In this paper, the improved Static Chamber and Li8100 that used to monitor soil Carbon Flux are introduced. Through continuously monitoring from July to November 2010, in northern Grass-type Lake-Baiyangdian demonstration, a series of conclusion are concluded about lake Carbon Flux : the day-variation of Carbon Fluxes chenged significantly, and varying followed time and temperature, the highest Carbon Flux is consistent to the highest temperature; the rule of day-variation is similar to aforesaid the three months(except special days), but Carbon Fluxes are not same, August>October> November. © (2012) Trans Tech Publications, Switzerland.


Wang T.-M.,Beijing Normal University | Wang T.-M.,Chinese Research Academy of Environmental Sciences | Wang T.-M.,State Environment Protection Key Laboratory of Regional Eco Process and Function Assessment | Wang Y.-Y.,Beijing Normal University | And 5 more authors.
Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis | Year: 2011

Fluorescence characterization of soil dissolved organic matter (DOM), which is one of the most important indexes concerning study on soil organic matter, can be effected by freezing and thawing cycles. In this paper, the fluorescence characterization of black soil DOM under the effect of freezing and thawing cycles was studied, using three-dimensional excitation-emission-matrix fluorescence spectroscopic (EEM). Based on the transformation of fluorescence characterization, the influences of humification degree and active humus in black soil were analysed. The result showed, compared with untreated by freezing and thawing cycles, (1) The phenomena red-shift of UV fulvic-like was found in soil DOM. It meant that the aromatization and humification degree increased. (2) Protein-like fluorescence peak was observed in some soil samples, which meant microbial activity was enhanced. (3) Active humus and humification degree are the indexs of soil fertility. The content of TOC in the active humus rose, just the same as the value of humification degree. It meant that soil fertility was improved. (4) Compared with the ratio of UV: visible humic-like fluorescence (r(a,c)), there were positive correlations with the active humus and humification degree. It meant that r(a,c) of soil DOM was one of the indexs on active humus, humification degree and soil fertility effected by freezing and thawing cycles.


Yang Y.,Changzhou University | Li X.,Changzhou University | Wang Q.,Beijing Normal University | Wang Q.,Chinese Research Academy of Environmental Sciences | And 3 more authors.
Huanjing Kexue Xuebao/Acta Scientiae Circumstantiae | Year: 2014

In this study, we combine the Integrated Exposure Uptake Biokinetic Model (IEUBK) and the Adult Lead Model (ALM) with the methods of laboratory tests, questionnaires, and documents to determine environment references of Pb in soil based on health risk by the study on the pregnant woman and child in Wenling of Zhejiang Province. The reference values were 180 mg·kg-1 and 555.6 mg·kg-1, respectively, lower than the values of Britain and other developed countries. Two kinds of model parameters were analyzed by Monte Carlo to discuss the prediction impact by changes in one factor model. The sensitivity of the lead exposure in air and drinking water of IEUBK model were 50.8%. The maximum probability of geometric standard deviation of women blood lead concentration in AIM model was -39.6%, while the sensitivity value of target blood lead concentration (n) in protection group was -19.5%. Respiratory exposure was the most significant and widespread and its impact was higher than oral exposure according to sensitivity analysis results. However, oral exposure had higher levels of digestion and absorption which caused uncertainties to the model prediction. Optimization of model parameters improved the sensitivity of the prediction results, leading to more scientific and accurate prediction results and less uncertainty. This study provided theoretical basis for the formulation of the reference value of lead in contaminated soil. Moreover, further study is needed to examine the suitability of the results to Chinese people, as the lead exposure receptors in the model are American.


Yu Y.J.,Beijing Normal University | Yu Y.J.,South China Institute of Environmental Sciences | Wang Q.,Beijing Normal University | Wang Q.,Chinese Research Academy of Environmental Sciences | And 4 more authors.
Advanced Materials Research | Year: 2014

The sewage treatment industry intensively consumes energy, which results in high operating costs and aggravates the energy crisis in China to a certain extent. Therefore, the study of the energy consumption and conservation of sewage treatment processes is of high realistic significance. Domestic and overseas sewage treatment processes, their current status of energy consumption and energy audit, as well as the trend of sewage treatment processes and their energy conservation are explored to obtain theoretical enlightenment on the energy conservation, emission reduction, and sewage treatment recycling in China. The results show that the activated sludge process is mainly used in Chinese sewage treatment plants. The average energy consumption of all sewage treatments is 0.30 kWh/m3 in China. CASS achieved the lowest amount of average energy consumption at 0.24 kWh/m3. SBR obtained the largest energy consumption of 0.36 kWh/m3. The energy consumption is 0.06 kWh/m3 for sewage lifting, 0.178 kWh/m3 for sewage treatment, and 0.028 kWh/m3 for sludge treatment in China. © (2014) Trans Tech Publications, Switzerland.


Du J.,Chinese Research Academy of Environmental Sciences | Du J.,State Environment Protection key Laboratory of Regional Eco process and Function Assessment | Shu J.,Chinese Research Academy of Environmental Sciences | Shu J.,State Environment Protection key Laboratory of Regional Eco process and Function Assessment | And 2 more authors.
Shengtai Xuebao/ Acta Ecologica Sinica | Year: 2012

The accurate identification of areas of ecosystem degradation and an objective evaluation of the effects of ecological restoration projects is necessary for ecological management and planning at the landscape scale. Ecological degradation and ecological restoration are dynamic equilibrium processes, while degradation must be considered relative to the pristine state of the ecosystem, and need to be analyzed from a time series perspective. Satellite remote sensing is widely used in ecological monitoring and assessment, as it provides extensive coverage, good spatial and temporal continuity and a long time-series dataset. This paper proposes a method for the identification of areas of ecosystem degradation and ecosystem recovery using long time-series satellite remote sensing and precipitation data, which are integrated into trend analyses of the precipitation use efficiency (PUE) and a normalized difference vegetation index (NDVI). The PUE is calculated as the ratio of cumulative NDVI to precipitation. Significantly reduced PUE and NDVI values indicate that ecological degradation is occurring, while increasing PUE and NDVI values indicate ecological recovery. This method was applied to the headwater catchment of the Yellow River basin in China using Advanced Very High Resolution Radiometer NDVI data from 1982 to 2006 and meteorological data from the same time period. The annual PUE value was calculated using the cumulative NDVI and precipitation in the growing season for each pixel. A comparative analysis of the trends in PUE and NDVI was undertaken to detect areas of ecosystem degradation and restoration. The results show that: (i) The average PUE and NDVI values across the region increased slightly, and the area undergoing ecosystem rehabilitation during 1982-2006 comprised more than 80% of the study area. (ii) The degraded area, with significantly negative trends in the PUE and NDVI values, mainly occurred in the region surrounding Maduo County, Zaling and Eling lakes and Longyangxia Reservoir. Significant ecosystem recovery was found in southeast part of the study area, where strong positive trends were identified in the PUE and NDVI values. (iii) The areas with ecosystem degradation and restoration detected in this study were consistent with the current grassland degradation situation in the headwater catchment of the Yellow River basin, indicating that this method is reliable and could be applied to the evaluation of the regional ecosystem. (iv) The PUE value is partially dependent on changes in the precipitation, so false ecosystem degradation or ecosystem recovery trends may be identified caused by rapid increases and decreases, respectively, in the precipitation rate. For example, a decrease PUE in Xining City was partly caused by increased precipitation. Evaluating the trends in both PUE and NDVI may avoid the errors caused by using PUE as the only factor when evaluating ecosystem degradation and recovery. This method is simple, feasible, usable and practical, and the required data are easily accessible. This method allows ecosystem changes to be studied at the landscape scale, and can be used for a preliminary investigation prior to a large scale survey of ecological degradation or restoration. The results of this study suggest that evaluating the temporal change in PUE and NDVI may provide a useful large-scale indicator of landscape degradation or recovery at decadal time intervals. We recommend the broad-scale application of this method, using temporal trends in the PUE and NDVI. This study provides a scientific basis for the planning and regulation of ecological reconstruction in the headwater catchment of the Yellow River basin, China.


Du J.,Chinese Research Academy of Environmental Sciences | Du J.,State Environment Protection Key Laboratory of Regional Eco Process and Function Assessment | Shu J.,Chinese Research Academy of Environmental Sciences | Shu J.,State Environment Protection Key Laboratory of Regional Eco Process and Function Assessment | And 8 more authors.
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | Year: 2012

It is practically significant for identification of different impacts of meteorological factors to study the response of reference crop evapotranspiration (ET 0) to climate change. Based on the daily data of ten weather stations across a large climatic gradient in upstream areas of the Yellow River basin, China for recent 50 years, ET 0 was estimated with the FAO56 Penman-Monteith (P-M) method. The P-M results and pan evaporation data were compared and the trends and response to climate change for reference crop evapotranspiration were calculated. The results show that the P-M method is suitable for study area. ET 0 occurs mainly from March to October in growing season, and decreases with the increase of altitude. Significant increasing ET 0 can be observed in most stations, where elevation is higher than 3000 m, and most stations in low elevation (<3000 m) show obvious decreasing ET 0. There are different change processes of ET 0 in high altitude and low elevation area. Daily sensitivity coefficients to air temperature, wind speed and relative humidity exhibit large fluctuations during the year, while small fluctuations for sunshine hours. ET 0 is insensitive to air temperature in winter and early spring, and the sensitivity gradually increases and achieves its maximum value in summer while opposite patterns were found for weed speed. Relatively strong negative sensitivity coefficients were obtained for relative humidity, and ET 0 is more sensitive to relative humidity in growing season. The long-term trend analyses of sensitivity coefficients show that the sensitivity coefficients to air temperature increased, while decreased for relative humidity in low elevation stations. Increased air temperature, sunshine hours and reduced relative humidity led to increasing ET 0 in high altitude area, whereas decreased ET 0 is dominated by reduced sunshine hours, wind speed and increased relative humidity in low elevation area. So the high altitude area in upstream areas of of the Yellow River basin is taken as the 'energy-limited' system and the low elevation area as the 'water-limited' system.


Du J.-Q.,Chinese Research Academy of Environmental Sciences | Du J.-Q.,State Environment Protection Key Laboratory of Regional Eco process and Function Assessment | Shu J.-M.,Chinese Research Academy of Environmental Sciences | Shu J.-M.,State Environment Protection Key Laboratory of Regional Eco process and Function Assessment | And 8 more authors.
Chinese Journal of Applied Ecology | Year: 2014

Consistent NDVI time series are basic and prerequisite in long-term monitoring of land surface properties. Advanced very high resolution radiometer (AVHRR) measurements provide the longest records of continuous global satellite measurements sensitive to live green vegetation, and moderate resolution imaging spectroradiometer (MODIS) is more recent typical with high spatial and temporal resolution. Understanding the relationship between the AVHRR-derived NDVI and MODIS NDVI is critical to continued long-term monitoring of ecological resources. NDVI time series acquired by the global inventory modeling and mapping studies (GIMMS) and Terra MODIS were compared over the same time periods from 2000 to 2006 at four scales of Qinghai-Tibet Plateau (whole region, sub-region, biome and pixel) to assess the level of agreement in terms of absolute values and dynamic change by independently assessing the performance of GIMMS and MODIS NDVI and using 495 Landsat samples of 20 km ×20 km covering major land cover type. High correlations existed between the two datasets at the four scales, indicating their mostly equal capability of capturing seasonal and monthly phenological variations (mostly at 0.001 significance level). Similarities of the two datasets differed significantly among different vegetation types. The relative low correlation coefficients and large difference of NDVI value between the two datasets were found among dense vegetation types including broadleaf forest and needleleaf forest, yet the correlations were strong and the deviations were small in more homogeneous vegetation types, such as meadow, steppe and crop. 82% of study area was characterized by strong consistency between GIMMS and MODIS NDVI at pixel scale. In the Landsat NDVI vs. GIMMS and MODIS NDVI comparison of absolute values, the MODIS NDVI performed slightly better than GIMMS NDVI, whereas in the comparison of temporal change values, the GIMMS data set performed best. Similar with comparison results of GIMMS and MODIS NDVI, the consistency across the three datasets was clearly different among various vegetation types. In dynamic changes, differences between Landsat and MODIS NDVI were smaller than Landsat NDVI vs. GIMMS NDVI for forest, but Landsat and GIMMS NDVI agreed better for grass and crop. The results suggested that spatial patterns and dynamic trends of GIMMS NDVI were found to be in overall acceptable agreement with MODIS NDVI. It might be feasible to successfully integrate historical GIMMS and more recent MODIS NDVI to provide continuity of NDVI products. The accuracy of merging AVHRR historical data recorded with more modern MODIS NDVI data strongly depends on vegetation type, season and phenological period, and spatial scale. The integration of the two datasets for needleleaf forest, broadleaf forest, and for all vegetation types in the phenological transition periods in spring and autumn should be treated with caution.

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