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Deng B.L.,Tianjin Environment Monitoring Center | Wang H.Z.,Tianjin Academy of Social science
Advanced Materials Research | Year: 2014

Climate change has been highlighted as an apparent and urgent issue in environmental research fields. Transport, as the third carbon emitter sector in China, is partly responsible for climate change. It is necessary to modify the existing Strategic Environmental Assessment (SEA) system for transportation planning so as to cope with the challenges of Climate Change. In this paper, we tried to integrate climate change consideration into SEA process, and proposed the framework and indicator system for SEA considering climate change. © (2014) Trans Tech Publications, Switzerland.

Wang X.-J.,Tianjin University | Gao X.,Tianjin Environment Monitoring Center | Zhai H.-Y.,Tianjin University
Xiandai Huagong/Modern Chemical Industry | Year: 2016

Ozone has been widely adopted in water and wastewater treatment. In this study, the effects of key parameters of ozone generator on the ozone bubble size, flow rate and concentration is deeply discussed. The results show that smaller aerator aperture results in lower oxygen output pressure and flow rate, which consequently decreases the bubble size and bubble rising velocity. It is useful to improve the dissolved ozone concentration. The bubble diameter, initial rising velocity and dissolved ozone concentration can reach 1.30 mm, 0.18 m/s and (26.84±0.20) mg/L, respectively, under the following conditions: microporous aerator, an oxygen output pressure of 0.1 MPa, a flow rate of 0.5 L/min and a temperature of 7℃. © 2016, China National Chemical Information Center. All right reserved.

Zhu X.,Tianjin University | Chen K.,Tianjin University | Yu H.,Tianjin University | Tang M.,Tianjin Environment Monitoring Center | Qu C.,Tianjin University
Chinese Journal of Environmental Engineering | Year: 2015

In this study, the daily monitoring data from August 2013 to May 2014 acquired through the Internet of Things for Environmental Protection of Tianjin were analyzed to identify the relationship between PM2.5 and the common pollutants (PM10, SO2, CO, O3, NO2). Linear multiple regression, quadratic multiple regression and multiple regression based on principal component analysis are tried to be used in the model, which describes the relationship in form of math. The correlation coefficients show the significant correlation between PM2.5 and the five kinds of common pollutants. The coefficients of PM10, SO2, and NO2 are 0.89±0.03, 0.63±0.09, 0.69±0.06, respectively. The concentration of PM2.5 can be estimated by the five kinds of common pollutants according to the evaluation of the model. Statistical result based on principal component analysis shows the best perfermance among three models with 0.85 goodness-of-fit level and 20% average forecasting error. ©, 2015, Science Press. All right reserved.

Cai H.,Mudanjiang Teachers College | Bian S.,Tianjin Environment Monitoring Center
Acta Theriologica Sinica | Year: 2015

Rodents were trapped using snap traps from 2011 to 2013 at 31 sites in six habitats in the Tianjin Palecoast and Wetland Natural Reserve (TPWNR)and ten environmental variables were recorded for each site. In total, 157 individuals were captured comprising 7 species. The total trap capture success rate was 1.69%. There were three dominant rodents: Apodemus agrarius, Rattus norvegicus, and Cricetulus triton, for which trap capture successes were 0.59%, 0.25%, and 0.23%, respectively. The trap capture success rates, species richness, Shannon and Pielou index were significantly difference among the six habitats. The highest trap capture successes were found in areas with human habitation and cropland, followed by water's edge; the remaining habitats were low. The highest values for both species richness and Shannon index were found in human inhabited areas and cropland, and the lowest value were found in alkali area habitat. The Pielou index was high in different habitats except of the water's edge habitat. These results indicate that there was significant variation among the rodent communities in TPWNR. Such variations were controlled by environmental factors. The result of redundancy analysis with forward selection indicated that distance to crops, herbaceous coverage, water salinity and shrub height played key roles in defining the structures of rodent communities in TPWNR. ©, 2015, Science Press. All right reserved.

Ran X.,Ocean University of China | Ran X.,State Oceanic Administration | Yu Z.,Ocean University of China | Yao Q.,Ocean University of China | And 3 more authors.
Biogeochemistry | Year: 2013

A mass balance of dissolved silica (DSi) based on daily measurements at the inflow and outflow of the Three Gorges Reservoir (TGR) in 2007 and a more precise budget, with inflow, outflow, primary production, biogenic silica (BSi) settlement, dissolution of BSi in the water column and flux of DSi at the sediment-water interface in the dry season (April) of 2007 were developed. We address the following question: How much does the Three Gorges Dam (TGD) affect silica transport in the TGR of the Changjiang River (Yangtze River)? The DSi varied from 71. 1 to 141 μmol/l with an average of 108 μmol/l, and it ranged between 68. 1 and 136 μmol/l, with an average of 107 μmol/l in inflow and outflow, respectively, in the TGR in 2007. The linear relationship of DSi between inflow and outflow water is significant (r = 0. 87, n = 362, p < 0. 01). Along the main stream of the TGR, the DSi concentration decreases with an average concentration of 84. 0 μmol/l in the dry season. However, the stratification of DSi was not obvious in the main channel of the TGR in the dry season. The BSi is within the range of 0. 04-5. 00 μmol/l, with an average concentration of 2. 1 μmol/l in the main channel of the TGR, while it is much higher in Xiangxi Bay (1. 30-47. 7 μmol/l, 13. 1 μmol/l) than in the main stream of the TGR and the other bays. After the third filling of the TGR, approximately 3. 8% of the DSi was retained by the TGR based on a 12-month monitoring scheme in 2007, which would slightly reduce nutrient fluxes of the Changjiang River to the East China Sea (2%). DSi was lost during January to June and November, whereas the additions of DSi were found during the other months in 2007. The budget results also indicate that there is a slight retention of DSi. The retention of DSi in the reservoir is approximately 2. 9%, while BSi is approximately 44%. Compared with the total silica load, the retention of DSi and BSi in the reservoir is only 5. 0% in the dry season. With its present storage capacity, the reservoir does not play an important role as a silica sink in the channel of the TGR. The DSi load is significantly related to discharge both in inflow and outflow waters (p < 0. 01). DSi retention, to some extent, is the runoff change due to impoundment. © 2012 Springer Science+Business Media B.V.

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