基于全球一体化的中原城市群城市竞争力研究

全球化背景下，城市群主导世界经济的趋势不可阻挡，关于城市群的研究随之也越来越受到人们的重视。近几年，中原城市群悄悄崛起，但只是一个雏形，还存在很多问题。为了更好的促进中原城市群的发育，特别是加强城市群内部各城市发挥特长、合理分工、优势互补，进而提升中原地区区域经济的发展水平，文章选用了九大类44项城市竞争力指标，建立了城市竞争力的指标体系，从定量的角度对中原城市群的城市竞争力进行了排序、对比、分析，其城市竞争力排名依次是郑州、济源、洛阳、焦作、漯河、新乡、许昌、平顶山及开封。得到的结论如下：(1)首位城市竞争力强，但还没有发挥核心城市的作用。(2)工业型的城市经济实力竞争力强。(3)农业型城市的经济竞争力较弱。(4)产业竞争力和资金实力是影响城市综合竞争力的主要因子。(5)个别城市的单项指标存在异常点，显现出其优劣势。最后根据分析结果，笔者提出了四点优化对策，为城市群中的城市定位、产业分工、资源优化配置及相应区域互动政策的制定提供决策依据。     

长江三峡GPS处理结果和应变背景场

采用BerneseGPSSoftware 4 .2对长江三峡工程诱发地震监测系统GPS监测网络 1998～ 2 0 0 3年的 6期观测数据进行了处理 ,结果表明 ,三峡库区与华南块体的水平相对运动在 0～ 3mm/a(± 0 .1～± 2 .0mm/a) ;蓄水导致的垂直形变区域主要集中在茅坪 香溪 巴东库段 ,近岸点垂直沉降的量级在 10～ 35mm左右 ,最大峰值区域香溪约 35mm(± 8.6mm) ,垂直形变沿远离库中心方向迅速衰减。采用贝塞尔双三次样条函数模型拟合该地区的应变率 ,推算各类水平应变场 ,结果表明 ,蓄水前各种应变背景在 10 -9/a～ 10 -10 /a量级。作为构造稳定地区 ,三峡库区近期因蓄水导致大规模形变 ,从而诱发中强地震的可能性不大     

利用AMTIS数据反演植被和土壤温度

遥感陆面温度 (LST)是目前遥感界面临的重要课题 ,组分温度反演则为LST反演的主攻目标。如果混合像元组分间的温度及发射率存在明显差别 ,就可以从多角度热辐射亮度变化中分离出组分温度的信息。在热辐射矩阵模型的基础上 ,讨论了确定可反演参数和反演组分温度的方法 ,并以AMTIS多角度热红外图像为数据源 ,在进行几何和大气纠正后 ,尝试利用矩阵反演方法分解混合像元中的植被和土壤温度。误差分析表明土壤温度反演结果较好 ,但植被温度的反演精度不高     

基于方差分量估计的自适应融合导航

多源传感器观测信息的精度一般不一致,利用方差分量估计理论可以合理地顾及各传感器观测信息在融合导航解中的权比.首先给出基于多源观测信息的融合导航解算模式,进而基于方差分量估计讨论了各传感器观测信息在融合导航解中的合理平衡问题,然后应用自适应因子顾及动力学模型预报信息的贡献,给出了计算过程,并利用模拟数据进行了试算与比较.     

Slow mass movement in the Kangchenjunga area, eastern Nepal Himalaya

Abstract   The rates of the accumulated and continuous displacement of solifluction lobes in the Kangchenjunga area, eastern Nepal Himalaya, were determined using glass fiber tubes and a strain probe. Ground temperature, precipitation and soil moisture were monitored at two sites, whose altitude differed by approximately 100 m, to understand the solifluction process. The average movement rate of the glass fiber tubes on a 31° slope at altitudes of 5412–5414 m a.s.l. was approximately 11 mm/year, being almost threefold greater than that observed on a 22° slope at 5322–5325 ma.s.l. There was no significant difference in the depth of displacement at these sites. The continuous displacement measurement near the ground surface at 5414 m showed permanent downslope movement from early July. Such movement may be attributed to additional moisture supply during the monsoon season. The amplitude of the displacement cycle was highest at the ground surface, and decreased to virtually zero at and below 20 cm in depth. Probable factors leading to the relatively slow rates of downslope displacement at the surface and depth at the studied altitudes are the lack of concurrence of the freeze–thaw cycles and the high moisture condition in the soil, and the low moisture retention capacity of the soil because of steep slopes and superficial desiccation. The rate of displacement may be more pronounced at altitudes above 5600 m because of the freeze–thaw cycles during the summer season.     

锦州地震台体积式钻孔应变仪的映震情况

论述了张北MS6.2、沈阳ML4.1、内蒙古ML5.9、日本北海道MS8.0、俄蒙中交界MS7.9、青海昆仑山MS8.1地震前后,锦州地震台体积式钻孔应变仪观测震前异常的变化规律。通过计算潮汐因子、振幅因子、3点线性平滑滤波残差值等方法,识别异常。结果表明,体应变异常资料与地震有一定的相关性。     

Nonlinear free thermal convection in a spherical shell:A variable viscosity model

Introduction The velocity field of surface plate motion can be split into a poloidal and a toroidal parts.At the Earth′s surface,the toroidal component is manifested by the existence of transform faults,and the poloidal component by the presence of convergence and divergence,i.e.spreading and subduc-tion zones.They have coupled each other and completely depicted the characteristics of plate tec-tonic motions.The mechanism of poloidal field has been studied fairly clearly which is related to …     

Primary component analysis method and reduction of seismicity parameters

Introduction Data mining (SHAO and YU, 2003) is a new kind of technique developed with database and artificial intelligence in recent years, which processes the data in the database to abstract the im- plied and pre-unknown, but potentially useful information and knowledge from large amounts of incomplete, noisy, blurring and stochastic data. For data mining, data purging is an important link beforehand that includes eliminating noise, making up lost domain, and deleting ineffective data, as…     

Assessing the Comparability of Ammonium,Nitrate and Sulfate Concentrations Measured by Three Air Quality Monitoring Networks

Airborne fine particulate matter across the United States is monitored by different networks, the three prevalent ones presently being the Clean Air Status and Trend Network (CASTNet), the Interagency Monitoring of PROtected Visual Environment Network (IMPROVE) and the Speciation and Trend Network (STN). If combined, these three networks provide speciated fine particulate data at several hundred locations throughout the United States. Yet, differences in sampling protocols and samples handling may not allow their joint use. With these concerns in mind, the objective of this study is to assess the spatial and temporal comparability of the sulfate, nitrate and ammonium concentrations reported by each of these networks. One of the major differences between networks is the sampling frequency they adopted. While CASTNet measures pollution levels on seven-day integrated samples, STN and IMPROVE data pertain to 24-hour samples collected every three days. STN and IMPROVE data therefore exhibit considerably more short-term variability than their CASTNet counterpart. We show that, despite their apparent incongruity, averaging the data with a window size of four to six weeks is sufficient to remove the effects of differences in sampling frequency and duration and allow meaningful comparison of the signals reported by the three networks of concern. After averaging, all the sulfate and, to a lesser degree, ammonium concentrations reported are fairly similar. Nitrate concentrations, on the other hand, are still divergent. We speculate that this divergence originates from the different types of filters used to collect particulate nitrate. Finally, using a rotated principal component technique (RPCA), we determined the number and the geographical organization of the significant temporal modes of variation (clusters) detected by each network for the three pollutants of interest. For sulfate and ammonium, the clusters’ geographical boundaries established for each network and the modes of variations within each cluster seem to correspond. RPCA erformed on nitrate concentrations revealed that, for the CASTNet and IMPROVE networks, the modes of variation do not correspond to unified geographical regions but are found more sporadically. For STN, the clustered areas are unified and easily delineable. We conclude that the possibility of jointly using the data collected by CASTNet, IMPROVE and STN has to be weighed pollutant by pollutant. While sulfate and ammonium data show some potential for joint use, at this point, combining the nitrate data from these monitoring networks may not be a judicious choice.     

Spatial character of the gaseous and particulate state compound correlation of urban atmospheric pollution in winter and summer

The spatial/temporal variation information of atmospheric dynamic-chemical processes at observation site points of the "canopy" boundary of Beijing urban building ensemble and over urban area "surface", as well as the seasonal correlation structure of the gaseous and particulate states of urban atmospheric pollution (UAP) and its seasonal conversion feature at observation points are investigated, using the comprehensive observation data of the Beijing City Air Pollution Observation Experiment (BECAPEX) in winter and summer 2003 with a "point-surface" combined research approach. By using "one dimension spatial empirical orthogonal function (EOF)" principal component analysis (PCA) mode, the seasonal change of gaseous and particulate states of atmospheric aerosols and the association feature of pollutant species under the background of the complicated structure of urban boundary layer (UBL) are analyzed. The comprehensive analyses of the principal components of particle concentrations,gaseous pollutant species, and meteorological conditions reveal the seasonal changes of the complex constituent and structure features of the gaseous and particulate states of UAP to further trace the impact feature of urban aerosol pollution surface sources and the seasonal difference of the component structure of UAP. Research results suggest that in the temporal evolution of the gaseous and particulate states of winter/summer UAP, NOx, CO, and SO2 showed an "in-phase" evolution feature, however, O3 showed an "inverse-phase" relation with other species,all possessing distinctive dependent feature. On the whole, summer concentrations of gaseous pollutants CO, SO2, and NOx were obviously lower than winter ones, especially, the reduction in CO concentration was most distinctive, and ones in SO2 and NOx were next. However, the summer O3 concentration was more than twice winter one. Winter/summer differences in PM10and PM2.5 particle concentrations were relatively not obvious, which indicates that responses of PM10 and PM2.5 particle concentrations to the difference of winter/summer heating period emission sources are far less distinctive than those of NOx, SO2, and CO. The correlation feature of winter/summer gaseous and particulate states depicts that both PM10 and PM2.5 particles were significantly correlated with NOx, and their correlations with NOx are more significant than those with other pollutants. Through PCA, it is found that there was a distinctive difference in the principal component combination structure of winter/summer PM10 and PM2.5 particles: SO2 and NOx dominated in the principal component of winter PM10 and PM2.5 particles; while CO and NOx played the major role in the principal component of summer PM10 and PM2.5 particles. For winter/summer PM10 and PM2.5 particles, there might exist the gaseous and particulate states correlation structures of different "combinations" of such dependent pollutant species. Research results also uncover that the interaction processes of gaseous and particulate states were also related with the vertical structure of UBL, that is to say, the low value layer of UBL O3 concentration was associated with the collocation of atmospheric vertical structures of the low level inversion,inverse humidity, and small wind, which depicts summer boundary layer atmospheric character, i.e.the compound impact of the dependent factor "combination" of wind, temperature, and humidity elements and their collocation structure on the variations of different gaseous pollutant concentrations. Such a depth structure of the extremely low value of O3 concentration in the UBL accords with its "inverse-phase" relation with other gaseous pollutant species. The PCA of meteorological factors associated with PM10 and PM2.5 concentrations also reveals the sensitivity of PM10 and PM2.5 concentration to the combinatory feature of local meteorological conditions.