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In order to provide a sound basis for the performance evaluation of a local government’s air pollution prevention and abatement measures, the mass concentrations of PM2.5 and PM10 and the concentrations of different sized particles were measured in August 2013. Meanwhile, the influencing factors and sources of atmospheric particulate matters were analyzed by combining meteorological factors and gaseous pollutants. The results indicated that PM2.5 and PM10 in Zhuzhou were (30.3±12.2) μg·m⁻³ and (56.4±26.6) μg·m⁻³, respectively. The mean values of the particle number concentration in the size range of 0.5~1 μm and 1~2.5 μm on sunny days were (121.2±75.9) cm⁻³ and (6.8±3.7) cm⁻³, respectively, whereas in the rainy days they sharply increased to (868.7±262.1) cm⁻³ and (347.9±238.6) cm⁻³, which accounted for 71.0% and 28.4% of the total number of concentrations, respectively. Backward trajectory analysis demonstrated that the air masses in Zhuzhou city mainly came from three directions: southeast (52.2%), southwest (24.7%), and northeast (23.1%). Although accounting for a minor fraction, the northeast air mass had the largest effect on particle concentrations in Zhuzhou and also carried a lot of gaseous primary pollutants.
Based on the data of population size, industrial development, energy consumption and technological level from 2013 in the Beijing-Tianjin-Hebei region, the fairness of PM₂.₅ pollution emissions were analyzed using Gini coefficient and contribution coefficient. In addition, a reduction allocation plan of PM₂.₅ concentration by 2020 in 13 cities was determined according to a minimized model of Gini coefficient model. The results showed that: (1) Gini coefficients of industrial development and technological level were greater than 0.4, implying that the PM₂.₅ pollution emissions in the region were significantly unfair from the perspective of industry and technology, especially in the aspect of technological level. (2) The spatial distribution of industrial and technological contribution coefficients presented a downward trend from Beijing and Tianjin to the periphery, and cities in Hebei Province were central to the unfairness of PM₂.₅ pollution emissions across the whole region. (3) The reduction values of PM₂.₅ concentration were between 16.7 1μg/m³ and 57.49 μg/m³, and a reduction allocation plan of PM₂.₅ concentration could improve the overall fairness of PM₂.₅ pollution emissions in the Beijing-Tianjin-Hebei region, but the unfairness of PM₂.₅ pollution emissions would not change dramatically.
Euphorbia pekinensis Rupr., which is also known as a medicinal plant, produces a large amount of alkaloids, phytosterols and triterpenes. In this study, we reported on the cDNA cloning and characterization of a novel squalene synthase (SQS) from E. pekinensis. Squalene synthase catalyzes the condensation of two molecules of farnesyl diphosphate (FPP) to produce squalene (SQ), the first committed precursor for sterol and triterpene biosynthesis. The full length cDNA named EpSQS (Genbank Accession Number JX509735) contained 1,614 bp with an open reading frame of 1,236 bp encoding a polypeptide of 411 amino acids. The deduced amino acid sequence of the EpSQS named EpSQS exhibited a high homology with other plant SQSs, and contained a single domain surrounded by helices. Phylogenetic analysis showed that EpSQS belonged to the plant SQS kingdom. Tissue expression analysis revealed that EpSQS expressed strongly in roots, weakly in stems and leaves, implying that EpSQS was a constitutive expression gene. The recombinant protein was expressed in Escherichia coli and detected by SDS-PAGE and western blot. The high performance liquid chromatography (HPLC) analysis showed that EpSQS could catalyze the reaction from farnesyl diphosphate (FPP) to squalene.
In this study, the comparative effects of the two disturbances (aquaculture and water level fluctuations) on macroinvertebrate communities were explored in two waterbodies connected with the reservoir system of Three Gorges Reservoir (TGR) in China. One water body called Gaoyang Bay which suffered organic pollution from intensive aquaculture. Another named Hanfeng Lake, where the effects of water-level fluctuations are obvious. The results showed that aquaculture could significantly affect the chemical forms of nutrients, decrease the α-diversity and increase the β-diversity of macroinvertebrates although the communities in the treatment area in Gaoyang Bay were not fundamentally changed comparing to the control area in the same bay. The densities of macroinvertebrates in the treatment area were significantly lower than that of the control area. The composition of functional feeding groups in the treatment area was close to that in Hanfeng Lake, but obviously different from that in the control area in Gaoyang Bay and the collectors and predators dominated the communities in this control area with the highest percentages. Although water-level fluctuations had negative effects on the communities by decreasing the α-diversity and increasing the β-diversity, which were confirmed by the values of Simpson index, Shannon-Wiener index and Harrison's index in the control area of Gaoyang bay and Hanfeng Lake, the adverse effects were relative low compared to aquaculture. In the bays of TGR, the small-scale disturbance (aquaculture activities) had more significant negative effects compared to the big-scale disturbance (water-level fluctuations related to dam operation of TGR).
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