Correlation of atmospheric visibility with chemical composition of Kaohsiung aerosols

The objective of this study was to investigate the correlation of visibility with chemical composition of Kaohsiung aerosols. Daytime visibility was observed around noon at two observation sites in metropolitan Kaohsiung, Taiwan in the years of 1999 and 2000. Both seasonal and diurnal variation patterns of visibility were observed in the region. Ambient aerosols were sampled and analyzed for 11 constituents, including water-soluble ionic species (Cl⁻, NO₃⁻, SO₄⁻², NH₄⁺, K⁺, Na⁺, Ca⁺², and Mg⁺²) and carbonaceous contents (OC, EC, and TC), to characterize the chemical composition of Kaohsiung aerosols. Furthermore, a stepwise multiple linear regression model was developed to elucidate the influence of aerosol species on visibility impairments. The results showed that sulfate was the dominant species that affected both light scattering coefficient and visibility. On average, the percentage contributions of visibility degrading species to light scattering coefficient were 29% for sulfate, 28% for nitrate, 22% for total carbon, and 21% for PM_2.5-remainder. An empirical regression model of visibility based on sulfate, nitrate, and relative humidity was also developed. The model showed that sulfate in PM_2.5 was the most sensitive species to visibility variation, suggesting that the reduction of sulfate in PM_2.5 could effectively improve the visibility of metropolitan Kaohsiung. During the investigation period, an event of Asian dusts intruded metropolitan Kaohsiung and dramatically increased the aerosol loadings, especially in the coarse particles. However, local visual air quality did not degrade accordingly during the Asian dust event because both visibility and light scattering coefficient are affected mainly by the fine particles. The results are discussed in detail in the paper.     

大数据环境下道路场景高时空分辨率众包感知方法EI北大核心CSCD

道路场景作为人类发展演变中最重要、最复杂、最典型的载体之一,是道路基础设施与活动行为共同构成的综合体,链接和构建“人地关系”。道路场景感知从二维抽象简略到三维精细丰富、从静态过去式向动态现在时发展,成为智慧城市、智能交通、无人驾驶的关键技术支撑,是我国新型城镇化战略、交通强国战略的核心技术保障。本文立足于时空交通大数据,提出基于道路场景静态基础设施“形”和动态活动行为“流”的高时空分辨率道路场景感知方法。该方法从静态路网“形”角度,以“点-线-面-体”等要素为研究脉络,构建高精度道路地图众包感知的理论体系;在活动行为“流”感知上,突破传统的点模式分析局限,发展了道路网络空间活动流的时空建模与多尺度分析方法。本文揭示了静态基础设施“形”结构与动态活动行为“流”模式交互作用下的道路场景演化规律,形成以“形”控“流”、借“流”定“形”、“形”“流”叠置的高时空精度道路场景众包感知理论体系,为智慧城市、智能交通的发展提供核心技术与数据支撑。     

Application of back-propagation networks in debris flow prediction

Debris flows have caused serious loss of human lives and a lot of damage to properties in Taiwan over the past decades. Moreover, debris flows have brought massive mud causing water pollution in reservoirs and resulted in water shortage for daily life locally and affected agricultural irrigation and industrial usages seriously. A number of methods for prediction of debris flows have been studied. However, the successful prediction ratio of debris flows cannot always maintain a stable and reliable level. The objective of this study is to present a stable and reliable analytical model for occurrence predictions of debris flows. This study proposes an Artificial Neural Networks (ANN) model that was constructed by seven significant factors using back-propagation (BP) algorithm. These seven factors include (1) length of creek, (2) average slope, (3) effective watershed area, (4) shape coefficient, (5) median size of soil grain, (6) effective cumulative rainfall, and (7) effective rainfall intensity. A total of 178 potential cases of debris flows collected in eastern Taiwan were fed into the ANN model for training and testing. The average ratio of successful prediction reaching 93.82% demonstrates that the presented ANN model with seven significant factors can provide a stable and reliable result for the prediction of debris flows in hazard mitigation and guarding systems.     

关于氡测量标定装置(氡室)和测量单位的统一

本文介绍了作者研制的8505—I型氡室,该氡室可用于准确和快速标定多种测氡装置。作者提出了相应的标定方法,并测定了野外常用的10种氡探测器的标定系数。根据法定计量单位选用了贝克(Bq)和贝克/升(Bq/L)。相应作为各种氡测量的[放射性]活度单位和氡浓度单位。     

Molecular fossil and paleovegetation records of paleosol S4 and adjacent loess layers in the Luochuan loess section, NW China

Using gas chromatography-mass spectrometry (GC-MS) technique, a series of biomarkers were identi- fied, including n-alkanes, n-alkane-2-ones, isoprenoid etc. from the loess-paleosol samples collected from the S4 and adjacent L5, L4 of the Luochuan loess section, Northwestern China. Based on these data, especially n-alkanes and high-resolution magnetic susceptibility and grain size data, the pa- leoenvironment and paleovegetation history during S4 was reconstructed. The CPI (Carbon Predomi- nance Index) and correlation between n-alkanes and magnetic susceptibility and grain size data dem- onstrated that the molecular fossils in paleosol and loess layers can reflect the vegetation condition during the loess-paleosol formation, if the allochthonous organic inputs could be excluded reasonably. The ACL (average chain length) index is correlated well with paleomagnetic susceptibility and grain size variations, displaying their good synchrony with warm and humid climate. However, it relatively lagged behind the paleomagnetic susceptibility and the grain size variations when the climate began to deteriorate. During the formation period of paleosol, the n-alkanes was dominated by C31 homologue, indicating that the primary organic input originated from herbs. Our study also demonstrated that the herbs were more flourish than wood plants in Loess Plateau, especially in the Luochuan area during the warm and humid phase, and there was no typical forest vegetation developed in the studied period.     

Mean flow and variability in the southwestern East Sea

The Ulleung Basin is one of three deep basins that are contained within the East/Japan Sea. Current meter moorings have been maintained in this basin beginning in 1996. The data from these moorings are used to investigate the mean circulation pattern, variability of deep flows, and volume transports of major water masses in the Ulleung Basin with supporting hydrographic data and help from a high-resolution numerical model. The bottom water within the Ulleung Basin, which must enter through a constricted passage from the north, is found to circulate cyclonically—a pattern that seems prevalent throughout the East Sea. A strong current of about 6 cms⁻¹ on average flows southward over the continental slope off the Korean coast underlying the northward East Korean Warm Current as part of the mean abyssal cyclonic circulation. Volume transports of the northward East Korean Warm Current, and southward flowing East Sea Intermediate Water and East Sea Proper Water are estimated to be 1.4 Sv (1 Sv=10⁻⁶ m³ s⁻¹), 0.8 Sv, and 3.0–4.0 Sv, respectively. Deep flow variability involves a wide range of time scales with no apparent seasonal variations, whereas the deep currents in the northern East Sea are known to be strongly seasonal.     

三塘湖盆地低熟油的发现及其地球化学特征

三塘湖盆地目前所发现的原油的C₂₉甾烷 20S/(20S +20R)值大部分小于 0.42,属于低 (未 )熟油的范畴。与国内外报道的低熟油相比,三塘湖盆地物性特征也具有高密度、高粘度及高含蜡量等特征,但其物性偏好。经油源分析,这些低熟油主要来源于上二叠统芦草沟组。该组烃源岩演化程度较低,有机质丰度较高,属较好生油岩。通过有机显微组分分析,发现芦草沟组烃源岩以富含腐泥无定形富氢显微组分而有别于三塘湖盆地其它低熟源岩。经热解分析,腐泥无定形是芦草沟组烃源岩主要生烃贡献者,并且其主生烃期Ro 在 0.35 %～ 0.6 %之间。因此,腐泥无定形低熟生烃是三塘湖盆地低熟油的主要生烃机制。另外,在三塘湖盆地原油以及芦草沟组源岩中都检测到 17α(H) 2 5 降霍烷系列化合物,说明三塘湖盆地的低熟油可能与陆源有机质细菌降解改造作用有关。     

CSS集群技术在地震核心网中的应用

随着网络虚拟化技术的发展,以及地震系统业务内容的扩展,原地震行业网络核心层从性能上已逐渐难以满足需求。为保障网络可靠高效运转,同时为满足地震行业网络零中断的需求,利用新一代CSS交换机集群技术,采用中间设备临时接管的方法,对地震核心网进行了平滑改造升级,通过升级简化了网络结构,提高了网络效能。     

嵌岩桩负摩阻力现场试验与计算方法研究

桩-土剪切位移对桩基负摩阻力发展有重要的影响。在既有研究的基础上,通过桩周土体沉降与桩身应变的监测结果建立了计算桩-土剪切位移量的方法。利用该方法对浅中层桩-土监测数据进行分析,确定了在桩顶自由条件下该试验场地桩-土剪切位移量在4~5 mm;对于深层桩-土没有达到该剪切位移量,负摩阻力则无法发挥至极值。根据负摩阻力的发挥特征,改进了规范中嵌岩桩负摩阻力的计算方法,该方法同时考虑了桩周土竖向有效应力与桩土剪切位移的影响。使用该方法计算的负摩阻力与实测结果较为吻合,获得的下拉荷载能够达到安全与经济的效果,可供工程设计参考、借鉴。