Accumulation of petroleum hydrocarbons and heavy metals in clams （Ruditapes philippinarum） in Jiaozhou Bay, China

Accumulation and distributions of aliphatic and polyaromatic hydrocarbons (PAHs) and heavy metals were measured in tissues of the clam Ruditapes philippinarum collected from 5 sites in Jiaozhou Bay, Qingdao, China. The concentrations of total aliphatic hydrocarbon and PAHs ranged from 570 to 2 574 ng/gdw (gram dry weight) and from 276 to 939 ng/gdw, in the most and least polluted sites, respectively. The bio-accumulation of hydrocarbons and PAHs in the clams appeared to be selective. Aliphatic hydrocarbons were predominantly represented by short chain (<nC₂₃) n-alkanes, suggesting that petroleum hydrocarbons were likely the major contamination source. The selective uptake of 3 and 4 ring PAHs, such as naphthalene, fluorene, phenanthrene, fluoranthene and pyrene, by the clams was probably related to the physiological and bio-kinetic processes that were energetically favorable for uptake of compounds with fewer rings. Accumulation of the metals Cd, Cu, Zn, Pb, Cr, Hg, and As in the clam tissues also showed high variability, ranging from 0.043 to 87 μg/gdw. Among the 7 detected metals, Zn, Cd, Cu, and As had a particularly high potential of accumulation in R. philippinarum. In general, a positive correlation was found between the tissue concentrations and sediment concentrations of hydrocarbons and of some metals. Our study suggests that moderate contamination with polyaromatic hydrocarbons, and low to moderate contamination with metals, currently exists for clam R. philippinarum in Jiaozhou Bay, in comparison with other regional studies. A long-term monitoring program is certainly needed for assessment of the potential ecological influence and toxicity of these contaminants of R. philippinarum in Jiaozhou Bay.     

Distribution of the nonlinear random ocean wave period

Because of the intrinsic difficulty in determining distributions for wave periods, previous studies on wave period distribution models have not taken nonlinearity into account and have not performed well in terms of describing and statistically analyzing the probability density distribution of ocean waves. In this study, a statistical model of random waves is developed using Stokes wave theory of water wave dynamics. In addition, a new nonlinear probability distribution function for the wave period is presented with the parameters of spectral density width and nonlinear wave steepness, which is more reasonable as a physical mechanism. The magnitude of wave steepness determines the intensity of the nonlinear effect, while the spectral width only changes the energy distribution. The wave steepness is found to be an important parameter in terms of not only dynamics but also statistics. The value of wave steepness reflects the degree that the wave period distribution skews from the Cauchy distribution, and it also describes the variation in the distribution function, which resembles that of the wave surface elevation distribution and wave height distribution. We found that the distribution curves skew leftward and upward as the wave steepness increases. The wave period observations for the SZFII-1 buoy, made off the coast of Weihai (37°27.6′ N, 122°15.1′ E), China, are used to verify the new distribution. The coefficient of the correlation between the new distribution and the buoy data at different spectral widths (ν=0.3−0.5) is within the range of 0.968 6 to 0.991 7. In addition, the Longuet-Higgins (1975) and Sun (1988) distributions and the new distribution presented in this work are compared. The validations and comparisons indicate that the new nonlinear probability density distribution fits the buoy measurements better than the Longuet-Higgins and Sun distributions do. We believe that adoption of the new wave period distribution would improve traditional statistical wave theory.     

Application of matter-element model in soil nutrient evaluation of ecological fragile region

On the basis of the soil environment investigation in Da'an City, Jilin Province, China, 40 soil samples from main land use types were obtained and tested by standard method. Soil organic matter (SOM), total N (TN), total P (TP), total K (TK), available N (AN), available P (AP) and available K (AK) were chosen as the evaluation factors. A regional soil nutrient evaluation model was developed based on the matter-element model. The results show that the soil samples with nutrient grade Ⅱ-Ⅴ respectively account for 10%, 30%, 32.5% and 27.5%, and those with grade Ⅳ and Ⅴ account for 60% in all samples. The relationship between soil nutrients and land types indicates that the nutrients of farmland are relatively good, with 41.7% of soil samples with the nutrient grade Ⅳ and Ⅴ. The nutrients of saline-alkali land and sandy land are the worst, with 100% of soil samples with the nutrient grade Ⅳ and Ⅴ. And the ratios of soil samples grade Ⅳ and Ⅴ in grassland and wasteland are respectively 62.5 % and 54.55%. Generally speaking, the soil nutrients status in Da'an City is poor, 60% of soil samples are in poor and extremely poor conditions, indicating that the soil has been severely eroded. Being a relatively superior evaluation method with more accurate resuits and spatial distribution consistency, matter-element analysis is more suitable for regional soil nutrient evaluation than previous models.     

四川汶川“5.12”地震滑坡堰塞湖遥感监测分析

运用可见光、雷达和航片等不同空间分辨率的多源遥感数据,对四川汶川"5.12"地震灾区因地震诱发形成的大型堰塞湖进行了遥感监测,对堰塞湖发生的地点、数量以及空间分布规律进行了讨论。重点对唐家山堰塞湖进行了动态监测,提取了其堰塞湖回水长度、水面面积与水量等信息,并对这一结果进行了详细分析,为地震滑坡堰塞湖科学处置与减灾决策提供了科学依据。     

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吉林省某锑矿分离砷的研究

采用以水玻璃、硫酸为主的组合抑制剂,浮砷抑锑。较好地解决了砷锑分离的难题,使锑的精矿含砷降到符合国家质量标准。     

吉南老岭地区控矿构造特征分析

吉南老岭地区矿产资源丰富,大中型矿床众多,是吉林省的主要成矿区带。本文主要研究大地构造背景和地壳的演化规律及本地区韧性断裂、脆性断裂、韧脆性断裂及变质变形作用等构造类型的特征,进而阐明这些构造对矿产的控制作用。     

谈早前寒武纪侵入岩定位、变形、变质的同期性

依据鲁西地区早前寒武纪花岗质侵入岩普遍具有塑性流变特征和退化变质特征,以及变质作用和变形作用相协调等现象,认为岩体的侵位与变形、变质是同一期构造岩浆作用形成的,是岩浆就位后逐渐冷凝过程中,在持续应力作用下发生的,与后期的地质构造作用无关;固态岩石只能发生脆性变形和局部的脆韧性变形。并从热力场、动力场和化学场的变化趋势对变形、变质作用的制约因素作了简要分析。     

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局部型地形因子并行计算方法研究

 随着分析区域的扩展及需求精度的提高,数据-计算密集型地形分析亟需通过并行化来满足用户的时间响应需求。局部型地形因子是以一定半径的分析窗口(通常为3×3)计算且具有单元计算结果独立性的地形信息,是数字地形分析的基本参数。本文在分析局部型地形因子串行算法特征的基础上,以坡度算法为样本,对局部型地形因子的并行计算方法进行了深入研究。从数据并行的角度,对并行计算环境下的数据划分粒度、方式及结果融合策略进行了分析,构建了局部型地形因子的并行计算方法。利用SRTM陆地表面地形DEM数据,设计了坡度并行计算的实验以验证其方法的正确性和实用性。实验结果表明,本文提出的并行计算方法顾及了任务、数据及计算环境,可快速对局部型地形因子串行算法进行并行化改造,提高算法的执行效率,具有较好的并行性能。