宁波地区空气质量及大气自净能力海陆差异对比

以镇海、奉化分别作为宁波沿海和内陆空气质量代表站。基于代表站2013-2017年污染物资料和2015年12月至2017年2月冬季激光雷达资料,对比分析宁波地区沿海和内陆站点的空气质量差异;利用NCEP的GDAS(Global Data Assimilation System)资料和ERA-Interim高分辨率再分析资料评估两地气溶胶来源及大气自净能力差异。结果表明:宁波沿海和内陆地区中度及以上污染主要集中于冬季,冬季首要污染物以PM2.5为主;镇海NO2浓度较奉化显著偏高,而两地PM2.5 和PM10 浓度差异较小。冬季镇海和奉化3km以下都存在消光系数大的气溶胶集中层,镇海3km内消光系数平均值较奉化偏高约40%。两地中度及以上污染时,镇海和奉化的气溶胶粒子主要来自宁波西北方向的内陆地区,比例分别为90%和63%,镇海地区其余10%左右来自近距离低空偏东气流的输送,而奉化地区有37%来自浙江西南部的短距离输送。冬季当宁波地区出现区域性优和中度以上污染时,浙江北部沿海分别盛行东北风和西北风,空气质量优时混合层内平均风速大于中度以上污染时。浙江省大气自净能力比值呈自西北向东南减小,宁波地区优等空气质量大气自净能力约为中度以上污染的 1.5倍。大气自净能力在不同空气质量等级下差异显著,可作为大气污染发生、发展和消退判定的参考依据。     

运城盆地秋冬季PM2.5传输特征和源区分析

利用2017-2019年空气质量监测数据,采用HYSPLIT后向轨迹模式、聚类分析、潜在源贡献因子分析法（PSCF）和浓度权重轨迹分析法（CWT）,对运城市秋冬季大气PM2.5传输路径、对应重污染的天气形势和潜在源区进行分析。结果表明：（1）运城近地层盛行偏东风时污染频率高,弱的偏东风和西南风时,污染物浓度较大。秋冬季PM2.5后向轨迹西北方向最多达53.53%,偏东方向最少为11.25%,偏西方向和西南方向介于两者之间,分别为16.61%和12.06%。（2）不同轨迹对应天气形势不同,西北和偏西轨迹下,500 hPa高度场上为两槽一脊或偏西气流,700～850 hPa受脊前西北气流影响,地面为高压前底部型或均压场型;西南轨迹下,500 hPa高度场上为偏西气流,700～850 hPa运城处于槽前西南气流,地面气压场为高压前底部（底部）或均压场。（3）运城PM2.5潜在源区主要位于陕西南部、四川东部和新疆东南、甘肃的东南部等地区,说明影响运城秋冬季PM2.5的浓度除了来自汾渭平原西南部的颗粒物区域输送,来自西北方向新疆、甘肃的远距离颗粒物传输也是重要来源。     

“一带一路”背景下的中国与巴基斯坦的贸易关系演进及其影响因素

中巴经济走廊是“一带一路”6大经济走廊之一,而贸易畅通是“一带一路”建设的核心环节。研究中巴贸易关系演变及其影响因素、分析其贸易潜力,对推进“一带一路”建设具有重要的示范作用。论文从中巴贸易发展态势、商品结构、空间格局等方面揭示中巴贸易关系,运用随机前沿引力模型分析中巴贸易关系的主要影响因素、并探析其发展潜力,以期为推进中巴经济走廊建设提供科学支撑。研究发现：① 中巴贸易发展迅速,中对巴贸易顺差持续扩大;中国主要出口机械及电气设备等资本密集型产品,主要进口纺织原料及纺织制品等初级产品和劳动密集型产品。② 中国各省份与巴基斯坦的贸易合作存在明显的空间差异,东部沿海省份与巴贸易联系较紧密,西部各省份除新疆外与巴基斯坦贸易额均较小。③ 中国多数省份对巴贸易商品结构发生显著变动,其中,新疆、山东等进出口商品结构多元的省份的变动相对较小。④ 中国各省份的经济发展水平和市场规模对中巴贸易拉动较强;海运距离对中巴贸易规模有显著的负向影响;领土接壤为中巴组织边境贸易提供了良好条件;铁路和水运口岸的建设对中巴贸易具有积极影响。⑤ 中国各省份与巴基斯坦均有较大贸易潜力,内蒙古、云南、广西、陕西等省份的合作潜力更明显。     

Identifying primary public transit corridors using multi-source big transit data

ABSTRACT

Effective public transit planning needs to address realistic travel demands, which can be illustrated by corridors across major residential areas and activity centers. It is vital to identify public transit corridors that contain the most significant transit travel demand patterns. We propose a two-stage approach to discover primary public transit corridors at high spatio-temporal resolutions using massive real-world smart card and bus trajectory data, which manifest rich transit demand patterns over space and time. The first stage was to reconstruct chained trips for individual passengers using multi-source massive public transit data. In the second stage, a shared-flow clustering algorithm was developed to identify public transit corridors based on reconstructed individual transit trips. The proposed approach was evaluated using transit data collected in Shenzhen, China. Experimental results demonstrated that the proposed approach is a practical tool for extracting time-varying corridors for many potential applications, such as transit planning and management.     

MARC: a robust method for multiple-aspect trajectory classification via space,time, and semantic embeddings

ABSTRACT

The increasing popularity of Location-Based Social Networks (LBSNs) and the semantic enrichment of mobility data in several contexts in the last years has led to the generation of large volumes of trajectory data. In contrast to GPS-based trajectories, LBSN and context-aware trajectories are more complex data, having several semantic textual dimensions besides space and time, which may reveal interesting mobility patterns. For instance, people may visit different places or perform different activities depending on the weather conditions. These new semantically rich data, known as multiple-aspect trajectories, pose new challenges in trajectory classification, which is the problem that we address in this paper. Existing methods for trajectory classification cannot deal with the complexity of heterogeneous data dimensions or the sequential aspect that characterizes movement. In this paper we propose MARC, an approach based on attribute embedding and Recurrent Neural Networks (RNNs) for classifying multiple-aspect trajectories, that tackles all trajectory properties: space, time, semantics, and sequence. We highlight that MARC exhibits good performance especially when trajectories are described by several textual/categorical attributes. Experiments performed over four publicly available datasets considering the Trajectory-User Linking (TUL) problem show that MARC outperformed all competitors, with respect to accuracy, precision, recall, and F1-score.     

2003-2017年北京市地表热力景观时空分异特征及演变规律

利用2003-2017年MODIS地表温度数据,分别从数量、形状和结构角度揭示北京市不同季相和昼夜间地表热力景观时空分异特征,并进一步通过热力等级变化图谱及质心迁移轨迹揭示城市热力景观空间演变规律,探究热力景观等级转换生态过程。结论如下：① 城市地表热力景观季节和昼夜空间特征差异显著;② 中温区在城市热环境中占主导地位。白天中温区是最不稳定的热力景观等级;夜间次低温区和次高温区不稳定性增加;③ 地表热力景观等级变化以稳定型占主,反复变化型和前期变化型次之。地表热力景观等级通常呈现逐级递增或递减规律,山区呈现逐级降温趋势,北部城郊—山地交错地带表现出次低温和中温的反复转向,南部地区有一定的升温趋势;④ 2003-2017年高温区面积增大且质心向城市中心集中,低温区质心向城市外围扩散。生态涵养发展区对北京市地表热力景观质心迁移贡献率最高。热力景观时空分异特征及演变规律可为有效缓解城市热岛效应提供管理决策支持。     

基于Ruger近似式预测裂缝型储层的可行性研究

叠前纵波方位各向异性检测裂缝是目前应用最为广泛的方法,该方法主要是利用AVAZ地震资料椭圆拟合的长轴与短轴信息来评价裂缝,该方法在具体应用时,认为裂缝型储层AVAZ响应特征的变化仅由各向异性参数决定,而没有考虑非各向异性参数的影响,从而引起裂缝评价的多解性。为提高该技术的裂缝评价精度,从模型分析入手,将模型中各向异性参数及岩性参数设置为概率密度分布函数,然后采用Monte Carlo随机方法进行叠前AVAZ正演模拟。首先,对各向异性参数对椭圆拟合的影响进行简单分析,得出各向异性参数γ对椭圆扁率B/A与各向异性因子B影响最大、δ次之、ε最小。然后,进一步重点分析不同标准差的速度与密度模型的B/A与B响应特征,得出地层的速度与密度的变化在较小范围内时,该技术评价裂缝才具有一定的可行性,其中,地层纵波和横波速度的变化（尤其是纵波速度）对叠前AVAZ响应影响较大,地层密度几乎没有影响,故当横向岩性变化较大时,该方法在评价裂缝型储层时的结果具有一定的不确定性。     

山西辛安岩溶泉形成条件及随机模型

本文详细分析了山西辛安岩溶泉的水文地质条件,并通过对泉域岩溶水的补给、径流、排泄条件的分析,将辛安泉域概化为单输入单输出线性时不变集中参数随机系统的概念模型。利用24年的水文序列资料进行基流分割,获得泉多年月平均流量过程曲线,求得泉年平均流量和年平均补给量。在此基础上,应用滑动平均模型（MA）,自回归—滑动平均模型（AR-MA）及泉流量调和分析—残差自回归等三个模型,对泉域地下水进行模拟,获得了满意的结果,不仅揭示了泉水动态特征,而且对泉流量动态进行了预报,为晋东南区域经济规划提供了有益资料。     

基于自发地理信息的人行道路信息提取

人类的行为轨迹可快速提取到车辆难以通行的人行道路以及人行道路设施等信息,这些信息是行人LBS的关键性元素,它的完备性程度决定了行人LBS服务质量的高低。本文使用志愿者数据集与百度地图,研究了一整套基于VGI数据的人行道路信息提取方法。通过轨迹数据清洗、道路几何路网提取、人行道路设施的检测与识别3个主要板块实现了人行道路信息的提取。算法在完成道路几何路网信息提取的同时,实现了人行横道、过街天桥、地下通道等道路设施信息的获取。     

Simulation of normal distributed smooth fields by Karhunen-Loéve expansion in combination with kriging

Simulation of multigaussian stochastic fields can be made after a Karhunen-Loéve expansion of a given covariance function. This method is also called simulation by Empirical Orthogonal Functions. The simulations are made by drawing stochastic coefficients from a random generator. These numbers are multiplied with eigenfunctions and eigenvalues derived from the predefined covariance model. The number of eigenfunctions necessary to reproduce the stochastic process within a predefined variance error, turns out to be a cardinal question. Some ordinary analytical covariance functions are used to evaluate how quickly the series of eigenfunctions can be truncated. This analysis demonstrates extremely quick convergence to 99.5% of total variance for the 2nd order exponential (‘gaussian’) covariance function, while the opposite is true for the 1st order exponential covariance function. Due to these convergence characteristics, the Karhunen-Loéve method is most suitable for simulating smooth fields with ‘gaussian’ shaped covariance functions. Practical applications of Karhunen-Loéve simulations can be improved by spatial interpolation of the eigenfunctions. In this paper, we suggest interpolation by kriging and limits for reproduction of the predefined covariance functions are evaluated.