A New Modification to the Chemical Mass Balance Receptor Model for Volatile Organic Compound Source Apportionment

In this study, a modification to the chemical mass balance (CMB) receptor model presented in an earlier work was expanded to account for the changes in volatile organic compound (VOC) source fingerprints due to atmospheric reactions of VOCs that take place after being emitted to the atmosphere. The photochemical reactions consume VOCs that participate in, causing changes in the source fingerprints. These changes are of considerable magnitude when the travel durations from the source to the receptor (measurement point) are considered. The current study focuses on expansion of the integrated reaction rates of VOCs with ambient reactive species such as OH ^? , O₃, NO₃, and O ^? in order to estimate the source emission profiles simultaneously at the receptor site. Two test cases with different travel times and with different ambient OH ^? , O₃, and NO₃ concentrations were also provided to compare the standard model, the modified model suggested in the previous work, and the current modification. F‐tests were also performed to determine whether the changes in source compositions are significant or not. The results from both the standard model and the modified model were evaluated in terms of χ², R², percent mass apportioned (MA), and a best fit (BF) measure. Maximum values of BF for the test cases from the three models were 0.70 ± 0.03, 0.74 ± 0.05, and 1.000 ± 0.00, respectively, indicating that the current modification increases the performance of two previous models and was better in explaining the effects of chemical reactions of VOCs.     

Biosorption of Cadmium(II) Ions by Citrus Peels in a Packed Bed Column: Effect of Process Parameters and Comparison of Different Breakthrough Curve Models

The efficiency of low cost citrus peels as biosorbents for removal of cadmium ions from aqueous solution was investigated in a fixed bed column, a process that could be applied to treat industrial wastewaters similar to commonly used ion exchange columns. Effluent concentration versus time profiles (i.e., breakthrough curves) were experimentally determined in a laboratory‐scale packed bed column for varying operational parameters such as flow rate (2, 9, and 15.5 mL/min), influent cadmium concentration (5, 10, and 15 mg/L), and bed height (24, 48, and 72 cm) at pH 5.5. Column operation was most efficient for empty bed contact times of at least 10 min, which were apparently necessary for mass transfer. While the sorption capacity was largely unaffected by operational variables, the Thomas (Th) rate constant increased with the flow rate, and slightly decreased with increasing column length. Three widely used semi‐mechanistic models (Th, Bohart–Adams, and Yoon–Nelson) were shown to be equivalent and the generalized model was compared with a two‐parameter empirical model (dose‐response). The latter was found to be able to better simulate the breakthrough curve in the region of breakthrough and saturation.     

Spatial analysis of the invasion of lionfish in the western Atlantic and Caribbean

Pterois volitans and Pterois miles, two sub-species of lionfish, have become the first non-native, invasive marine fish established along the United States Atlantic coast and Caribbean. The route and timing of the invasion is poorly understood, however historical sightings and captures have been robustly documented since their introduction. Herein we analyze these records based on spatial location, dates of arrival, and prevailing physical factors at the capture sights. Using a cellular automata model, we examine the relationship between depth, salinity, temperature, and current, finding the latter as the most influential parameter for transport of lionfish to new areas. The model output is a synthetic validated reproduction of the lionfish invasion, upon which predictive simulations in other locations can be based. This predictive model is simple, highly adaptable, relies entirely on publicly available data, and is applicable to other species.     

页岩孔隙演化及其与残留烃量的耦合关系：来自地质过程约束模拟实验的证据

加强页岩孔隙演化规律研究,特别是定量评价其与残留烃之间的关系对页岩油的勘探具有重要意义。采集鄂尔多斯盆地低成熟度湖相Ⅰ型富有机质页岩,通过地质条件约束(埋藏史、地层压力、地层水矿化度等)成岩物理模拟实验模拟页岩演化,利用压汞法、氮气吸附法和二氧化碳吸附法获得不同温压段页岩的比孔容、比表面积和孔径分布,结合氯仿沥青A抽提定量结果,确定孔隙演化规律及其与残留烃的关系。结果表明页岩大孔比孔容与残留烃含量先增加后减小,微孔和中孔的比孔容随着模拟实验温度的增加呈现先减小后增大。XRD分析显示黄铁矿含量控制大孔,有机质丰度和粘土含量控制微孔和中孔。微孔和中孔的比孔容增加为高—过成熟度阶段页岩气提供储集空间,大孔比孔容与残留烃含量变化一致,生油窗阶段大孔增加是页岩油的有利储集带。     

Data assimilation considerations for improved ocean predictability during the Gulf of Mexico Grand Lagrangian Deployment (GLAD)

Ocean prediction systems rely on an array of assumptions to optimize their data assimilation schemes. Many of these remain untested, especially at smaller scales, because sufficiently dense observations are very rare. A set of 295 drifters deployed in July 2012 in the north-eastern Gulf of Mexico provides a unique opportunity to test these systems down to scales previously unobtainable. In this study, background error covariance assumptions in the 3DVar assimilation process are perturbed to understand the effect on the solution relative to the withheld dense drifter data. Results show that the amplitude of the background error covariance is an important factor as expected, and a proposed new formulation provides added skill. In addition, the background error covariance time correlation is important to allow satellite observations to affect the results over a period longer than one daily assimilation cycle. The results show the new background error covariance formulations provide more accurate placement of frontal positions, directions of currents and velocity magnitudes. These conclusions have implications for the implementation of 3DVar systems as well as the analysis interval of 4DVar systems.     

Automatic representation and reconstruction of DBM from LiDAR data using Recursive Minimum Bounding Rectangle

Three-dimensional building models are important for various applications, such as disaster management and urban planning. The development of laser scanning sensor technologies has resulted in many different approaches for efficient building model generation using LiDAR data. Despite this effort, generation of these models lacks economical and reliable techniques that fully exploit the advantage of LiDAR data. Therefore, this research aims to develop a framework for fully-automated building model generation by integrating data-driven and model-driven methods using LiDAR datasets.The building model generation starts by employing LiDAR data for building detection and approximate boundary determination. The generated building boundaries are then integrated into a model-based processing strategy because LiDAR derived planes show irregular boundaries due to the nature of LiDAR point acquisition. The focus of the research is generating models for the buildings with right-angled-corners, which can be described with a collection of rectangles under the assumption that the majority of the buildings in urban areas belong to this category. Therefore, by applying the Minimum Bounding Rectangle (MBR) algorithm recursively, the LiDAR boundaries are decomposed into sets of rectangles for further processing. At the same time, the quality of the MBRs is examined to verify that the buildings, from which the boundaries are generated, are buildings with right-angled-corners. The parameters that define the model primitives are adjusted through a model-based boundary fitting procedure using LiDAR boundaries. The level of details in the final Digital Building Model is based on the number of recursions during the MBR processing, which in turn are determined by the LiDAR point density. The model-based boundary fitting improves the quality of the generated boundaries and as seen in experimental results, the quality depends on the average LiDAR point spacing. This research thus develops an approach which not only automates the building model generation, but also achieves the best accuracy of the model while utilizing only LiDAR data.     

Response Surface Modeling of Cu(II) Removal from Electroplating Waste by Adsorption: Application of Box–Behnken Experimental Design

The use of kaolinite‐based clay minerals as a low‐cost natural adsorbent for the removal of Cu(II) from electroplating waste leachate was studied. Batch experiments were conducted to determine the effects of varying adsorbent loading, initial pH, adsorbent dosage, and contact time. Box–Behnken design with three variables like initial pH, adsorbent dosage, and contact time at three different levels was studied to identify a significant correlation between the effects of these variables to the amount of Cu(II) adsorbed. The methodology identifies the principal experimental variables, which have the greatest effect on the adsorption process. After optimizing the input variables by using Simplex algorithm, the adsorption of Cu(II) was maximal (99.9% with a maximum (positive) standard deviation of 9.4) at pH 6.24, adsorbent dosage of 0.83 g L^?1, and contact time of 97 min, respectively. Furthermore, the experimental values are in good agreement with predicted values, the correlation coefficient and adjusted correlation coefficients were found to be 0.96 and 0.87, respectively.     

Assessment of Climate Change Impact on the Gharesou River Basin Using SWAT Hydrological Model

The evaluation of climate change and its side effects on the hydrological processes of the basin can increasingly help in dealing with the challenges that water resource managers and planners face in future courses. These side effects are investigated using the simulation of hydrological processes with the help of physical rainfall‐runoff model. Hydrological models provide a framework for examining the relationship between climate and water resources. This research aims at the investigation of the effect of climate change on the runoff of Gharesou, which is one of the main branches of the “Karkheh” River in Iran during the periods 2040–2069. To achieve this, the distributed hydrological model Soil and Water Assessment Tool (SWAT) – a model that is sensitive to the changes in land, water, and climate – has been used with the aim of evaluating the impact of climate change on the hydrology of the Gharesou Basin. For this reason, first, the continuous distributed model of rainfall‐runoff SWAT for the period 1971–2000 has been calibrated and validated. Next, with the aim of evaluating the impact of climate change and global warming on the basin hydrology for the period 2040–2069, HadCM3‐AR4 global climate model data under the A2 scenario – from the SRES scenario set‐haves been downscaled. Eventually, the downscaled climate data haves been introduced in the SWAT model, and the future runoff changes have been studied. The results showed that the temperature increases in most of the months, and the precipitation rate exhibits a change in the range of ±30%. Moreover, the produced runoff in this period changes from ?90 to 120% during different months.     

冰雷达探测数据处理方法研究——以南极冰盖Dome A地区的数据处理为例

提出了冰雷达数据处理的流程,详细论述了冰雷达数据处理中常规修正的关键技术：静态校正、增益控制、带通滤波以及偏移处理等。以中国第24次南极科学考察（CHINARE 24）所获取的Dome A 地区30 km×30 km范围冰雷达原始数据处理作为实例,提取得到了该区域冰盖内部等时层埋深以及冰盖的冰厚数据。通过插值展现了冰盖等时层以及冰岩界面的三维空间形态。结合该区域ICESat冰盖表面高程数据,构建出了Dome A地区涵盖冰盖表面、冰盖等时层以及冰岩界面形态特征的三维模型。     

网上全景多视点实时浏览与快速传输系统

设计了一个面向虚拟旅游场景的网上全景多视点实时漫游与传输系统。该虚拟旅游系统是基于Flash3D技术进行了构架设计,对海量虚拟旅游全景图片的传输模式和传输策略进行了优化调度,从而使得虚拟旅游场景的网上浏览和传输变得更为流畅。该优化调度策略在湛江虚拟旅游系统中得到了很好的运用。