Vertical structures of PM10 and PM 2.5 and their dynamical character in low atmosphere in Beijing urban areas

The vertical structures and their dynamical character of PM2.5 and PM10 over Beijing urban areas are revealed using the 1 min mean continuous mass concentration data of PM2.5 and PM10 at 8, 100, and 320 m heights of the meteorological observation tower of 325 m at Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP CAS tower hereafter) on 10―26 August, 2003, as well as the daily mean mass concentration data of PM2.5 and PM10 and the continuous data of CO and NO2 at 8, 100 (low layer), 200 (middle layer), and 320 m (high layer) heights, in combination with the same period meteorological field observation data of the meteorological tower. The vertical distributions of aerosols observed on IAP CAS tower in Beijing can be roughly divided into two patterns: gradually and rapidly decreasing patterns, I.e. The vertical distribution of aerosols in calm weather or on pollution day belongs to the gradually decreasing pattern, while one on clean day or weak cold air day belongs to the rapidly decreasing pattern. The vertical distributive characters of aerosols were closely related with the dynamical/thermal structure and turbulence character of the atmosphere boundary layer. On the clean day, the low layer PM2.5 and PM10 concentrations were close to those at 8 m height, while the concentrations rapidly decreased at the high layer, and their values were only one half of those at 8 m, especially, the concentration of PM2.5 dropped even more. On the clean day, there existed stronger turbulence below 150 m, aerosols were well mixed, but blocked by the more stronger inversion layer aloft, and meanwhile, at various heights, especially in the high layer, the horizontal wind speed was larger, resulting in the rapid decrease of aerosol concentration, I.e. Resulting in the obvious vertical difference of aerosol concentrations between the low and high layers. On the pollution day, the concentrations of PM2.5 and PM10 at the low, middle, and high layers dropped successively by, on average, about 10% for each layer in comparison with those at 8 m height. On pollution days, in company with the low wind speed, there existed two shallow inversion layers in the boundary layer, but aerosols might be, to some extent, mixed below the inversion layer, therefore, on the pollution day the concentrations of PM2.5 and PM10 dropped with height slowly; and the observational results also show that the concentrations at 320 m height were obviously high under SW and SE winds, but at other heights, the concentrations were not correlated with wind directions. The computational results of footprint analysis suggest that this was due to the fact that the 320 m height was impacted by the pollutants transfer of southerly flow from the southern peripheral heavier polluted areas, such as Baoding, and Shijiazhuang of Hebei Province, Tianjin, and Shandong Province, etc., while the low layer was only affected by Beijing's local pollution source. The computational results of power spectra and periods preliminarily reveal that under the condition of calm weather, the periods of PM10 concentration at various heights of the tower were on the order of minutes, while in cases of larger wind speed, the concentrations of PM2.5 and PM10 at 320 m height not only had the short periods of minute-order, but also the longer periods of hour order. Consistent with the conclusion previously drawn by Ding et al., that air pollutants at different heights and at different sites in Beijing had the character of "in-phase" variation, was also observed for the diurnal variation and mean diurnal variation of PM2.5 and PM10 at various heights of the tower in this experiment, again confirming the "in-phase" temporal/spatial distributive character of air pollutants in the urban canopy of Beijing. The gentle double-peak character of the mean diurnal variation of PM2.5 and PM10 was closely related with the evident/similar diurnal variation of turbulent momentum fluxes, sensible heat fluxes, and turbulent kinetic energy at various heights in the urban canopy. Besides, under the condition of calm weather, the concentration of PM2.5 and PM10 declined with height slowly, it was 90% of 8 m concentration at the low layer, a little lesser than 90% at the middle layer, and 80% at the high layer, respectively. Under the condition of weak cold air weather, the concentration remarkably dropped with height, it was 70% of 8 m concentration at the low layer, and 20%―30% at the middle and high layers, especially the concentration of PM2.5 was even lower.     

Thickness distribution and extent of sea ice and snow in Prydz Bay and surrounding waters observed in 2012/2013 austral summer

Three ship-based observational campaigns were conducted to survey sea ice and snow in Prydz Bay and the surrounding waters(64.40°S–69.40°S, 76.11°E–81.29°E) from 28 November 2012 to 3 February 2013. In this paper, we present the sea ice extent and its variation, and the ice and snow thickness distributions and their variations with time in the observed zone. In the pack ice zone, the southern edge of the pack ice changed little, whereas the northern edge retreated significantly during the two earlier observation periods. Compared with the pack ice, the fast ice exhibited a significantly slower variation in extent with its northernmost edge retreating southwards by 6.7 km at a rate of 0.37 km?d-1. Generally, ice showed an increment in thickness with increasing latitude from the end of November to the middle of December. Ice and snow thickness followed an approximate normal distribution during the two earlier observations(79.7±28.9 cm, 79.1±19.1 cm for ice thickness, and 11.6±6.1 cm, 9.6±3.4 cm for snow thickness, respectively), and the distribution tended to be more concentrated in mid-December than in late November. The expected value of ice thickness decreased by 0.6 cm, whereas that of snow thickness decreased by 2 cm from 28 November to 18 December 2012. Ice thickness distribution showed no obvious regularity between 31 January and 3 February, 2013.     

水牛蹄型深海集矿机履齿设计及牵引性能研究

作为深海采矿系统的重要组成部分,深海集矿机的技术研究和开发一直是许多国家的难题。为了提高深海集矿机在稀软沉积物上的牵引性能,基于水牛蹄的曲面结构特征和特殊几何结构,设计了一款仿水牛蹄蹄型履齿。以该款履齿的结构参数为研究对象,通过对朗肯被动土压力理论的优化,得到了仿水牛蹄蹄型履齿的牵引力解析解,建立了对应的履齿仿生参数对履齿牵引力的影响公式。结合正交试验方法进行了不同形式履齿在沉积物上运动的单、多履齿剪切试验,将仿水牛蹄蹄型履齿与直型履齿、仿水牛蹄轮廓履齿（另一种仿生履齿）进行对比试验,并通过模型车试验验证了该款履齿的可行性。结果表明：3种履齿中,仿水牛蹄蹄型履齿提供的最大牵引力最高。研究可为进一步优化仿水牛蹄蹄型履齿结构参数和提高深海稀软底质机械的牵引性能提供参考依据。     

内蒙古典型草原和草甸草原相对花粉产量重估

相对花粉产量（RPP）是利用地层花粉数据定量重建古植被的重要参数,但目前估算的不同地区同一植物类型的RPP多存在差异。为了解植被盖度计算方法对花粉产量的影响,本项研究利用卫星影像数字化重新计算了内蒙古锡林郭勒典型草原和乌拉盖草甸草原采样点周边100 m以外的植被数据,利用ERV模型重新估算了主要花粉类型的RPP,并运用景观重建算法（LRA）进行了检验。锡林郭勒典型草原ERV模型分析显示,ERV子模型1结合1/d距离加权法与植被-花粉数据拟合度最高,得到的相关花粉源范围（RSAP）为1470 m;以蒿属为参照种（RPP=1±0）,各科属RPP依次为藜科（0.53±0.03）、十字花科（0.17±0.01）、唐松草属（0.14±0.02）、菊科（0.09±0.01）、莎草科（0.08±0.006）、委陵菜属（0.07±0.01）、禾本科（0.050±0.003）。乌拉盖草甸草原ERV模型分析显示,ERV子模型1结合Prentice距离加权法与植被-花粉数据拟合度最高,得到的RSAP为770 m;以蒿属为参照种（RPP=1±0）,各科属RPP依次为藜科（5.85±0.58）、蓼科（5.27±0.37）、石竹科（5.15±0.47）、莎草科（4.16±0.13）、菊科（1.63±0.09）、百合科（0.49±0.08）、唇形科（0.38±0.06）、禾本科（0.200±0.004）。重估的RSAP和RPP均与首次估算时存在差异,表明植被盖度计算方法确实会影响RSAP和RPP。景观重建算法对RPP检验结果表明,卫星影像数字化估算的RPP重建的植被盖度与实际植被的相关性更高。

     

面向智慧城市的GIS框架

现有轨迹匹配方法具有一定局限性,其匹配精度无法满足车辆导航定位的需求。针对拓扑匹配方法对于起始匹配位置的依赖性,提出了顾及速度与航向信息的轨迹匹配方法。该方法综合利用速度、距离和航向约束改进起始匹配路段和起始位置的判定,并通过后续时刻车辆的正确匹配位置修正起始位置,避免了传统拓扑匹配方法中起始位置匹配错误导致的误差传递累积,提高匹配路段的准确性。同时以起始位置为基础,速度与时间信息为约束确定匹配点。为验证所提方法的有效性,选取多条复杂程度各异的路线进行实验,并与现有的几何匹配方法和拓扑匹配方法进行比较。实验结果表明,该方法在不同复杂程度的城市路网下具有良好的匹配效果,准确率可达93.53%。在匹配准确率方面优于现有的两种方法,在匹配效率方面能满足定位导航的需求。     

辽宁锦州市地质遗迹资源禀赋及保护性利用

地质遗迹资源是提高人类当前和将来生活质量最珍贵的、不可再生的自然遗产,其保护、利用与管理是地质遗迹可持续性发展的前提和基础。辽宁省锦州市地跨燕山余脉和辽西中生代盆地,长期的地质演化留下了丰富的地质遗迹资源,其中尤以典型地层剖面、古生物化石、花岗岩地貌、河流地貌景观和海岸线最具特色,典型地质遗迹特征是对重要地质事件与人类活动历史的响应。通过锦州地质遗迹资源专项调查,从遗迹特征、成因等角度,将锦州市地质遗迹资源分为两大类、七小类、十一亚类,共计238处,整体上类型多样、内涵独特、分布范围广。然而,由于基础数据不清、保护意识淡薄、投入资金有限、管理机制不健全等原因,锦州市内的地质遗迹正遭受或面临严重破坏。针对锦州市"山、海、城"旅游产业空间布局、打造精品旅游目的地、宜居城市、生态文明、乡村振兴建设与地质遗迹保护性利用中存在的问题,建立地质遗迹资源保护名录、科普基地、特色风景廊道、风景旅游区、特色小镇及地质文化村,形成多层次、多样化的保护性利用路径。     

基于均值漂移的粒子滤波算法设计及其在导航数据处理中的应用

针对标准粒子滤波算法中存在的计算量大和粒子的权值退化的缺陷,将均值漂移算法和PF算法进行融合,设计基于均值漂移搜索算法的粒子滤波新算法。该算法仍遵从粒子滤波算法的计算框架,基本原理是利用MS算法对粒子的聚类作用,将均值漂移思想融合到粒子滤波算法的重要性采样过程中,对粒子集进行确定性搜索,使每个粒子收敛于局部最优值,这样粒子的状态表示更接近真实的状态分布,因此只需较少的粒子数便可达到未嵌入MS的使用大量粒子数的粒子滤波状态估计的性能,从而在缓解粒子的权值退化的同时提高粒子滤波算法的实时性。大量的数值试验和对GPS/DR组合导航数据处理的结果验证了该方法的有效性。     

浙江省芳香植物资源的分布和开发

根据浙江省芳香植物的组成 ,及该区的地理条件和芳香植物分布规律 ,将其划分为 5个区 ,分别进行探讨并列出部分芳香植物作为各地开发利用时参考。     

地面沉陷对路基的破坏影响及其防治技术

根据地下资源开发地区岩层与地表移动机理，研究了地面沉陷时路基产生的破坏影响，分析、总结了路基沉陷特征，给出了确定路基和矿柱强度及稳定性的验算方法，以及路基出现坍塌或滑坡等灾害事故的评估方法，提出了地面沉陷区路基防治技术，并列举了治理路基沉陷的例子。     

青藏高原东部表层土壤色度的空间变化特征及其环境意义

认识青藏高原东部现代表土的色度特征及其空间分布,理解其与现代气候因子之间的联系,对于高原地区黄土-古环境重建和揭示第四纪环境变化历史具有重要意义。通过对研究区表层土壤色度的详细分析,对比现代气候资料,探讨了青藏高原东部表层土壤色度的空间变化特征及其环境意义。结果表明：① 高原东部表土色度参数空间变化特征差异显著,表现为随纬度升高,土壤亮度呈先减小后增大的趋势,而红度和黄度则逐步减小;随经度的升高,黄度先增大后减小,而红度值逐步减小;红度和黄度整体随着海拔上升而呈先减小后升高的特征。这些变化特征和差异是表土色度对高原东部复杂地理环境和水热条件变化响应的结果。② 在高原的干旱-半湿润区,土壤亮度对降水的响应敏感;红度和黄度对大尺度的温度变化响应较敏感,而较冷的环境下,红度对温度响应复杂,但与降水存在一定的联系。红度/黄度比值主要指示了气候控制下的赤铁矿和针铁矿的变化和竞争,对干旱-半湿润区域的降水变化响应较为敏感。青藏高原东部现代表土色度与气候密切相关,其空间变化特征一定程度上反映了该地区现代气候因子的空间变化;另一方面由于该区地形和气候复杂多变,部分色度指标与气候关系复杂,在重建青藏高原东部黄土古环境变化历史时需要谨慎。