基于GIS的石家庄市雾霾分析     

苏亚聪  史娟  徐爽 《北京测绘》2020,(2):233-237

为了得出雾霾气象成因机制、影响因素和时空分布特征,以石家庄市区与郊县为研究区域,将2013年9月至2016年12月石家庄市各市区、郊县的PM2.5历史监测数据中的有效数据进行了数据分析处理得到雾霾浓度数据,还有温度、降水、风速、地形和人口密度等数据,运用GIS分析的方法,模拟绘制石家庄雾霾的时空分布图、雾霾与各影响因子的专题对比图,得到雾霾形成机制的因子、雾霾的时空分布规律、雾霾季节变化特征、雾霾与地形间的关系等;运用数据分析软件OriginPro8.SR3分析雾霾浓度与风速数据、降雨数据、温度数据间的相关性。  相似文献   

北京市区春季燃烧源大气颗粒物的污染水平和影响因素   总被引：17，自引：6，他引：17  

刘大锰  马永胜  高少鹏  黄杰  安祥华 《现代地质》2005,19(4):627-633

以大气中PM2.5和PM10为研究对象,于2005-03-13—25共7天的时间内,在中国地质大学(北京)测试楼顶、首钢焦化厂和首钢东门设立3个采样点进行采样监测。结果表明:PM2.5和PM10质量浓度的日变化呈现一定规律性,在不同时段PM2.5和PM10的质量浓度不尽相同,且变化较大,在特定时刻出现峰值,主要受污染源排放和气象因素的控制;PM2.5和PM10质量浓度随气温的升高而降低,这与高温有利于颗粒物扩散、低温容易形成逆温层有关;在一定的相对湿度范围内(以大气中水汽不发生重力沉降为界限),PM2.5和PM10质量浓度与相对湿度呈正相关关系;而当发生降水时,由于水滴的冲刷和附带作用,PM2.5和PM10质量浓度降低;PM2.5和PM10质量浓度与风级呈明显的负相关关系。通过北京市与国内8个省会城市的PM2.5和PM10质量浓度的对比,发现北京市PM2.5和PM10污染比较严重,PM2.5和PM10质量浓度分别超过了1996年中国制定的PM10排放标准和1997年美国EPA制定的PM2.5排放标准。  相似文献   

杭州市区春节期间空气质量变化特点   总被引：11，自引：0，他引：11       下载免费PDF全文

洪盛茂 何曦祁国伟  孙鸿良王晓熊  陈超徐鸿 《气象科技》2003,31(6):340-344

分析近3年春节期间的空气质量资料，结果表明，杭州市区环境空气中PM10、SO2、NO2浓度较高，烟花爆竹燃放期间3种污染物出现高峰值，这与烟花爆竹燃放有关，PM25／PM10的比值高于年均值。  相似文献   

中心回线瞬变电磁法2.5维有限单元算法   总被引：23，自引：6，他引：23       下载免费PDF全文

王华军  罗延钟 《地球物理学报》2003,46(6):855-862

瞬变电磁法的野外资料解释基本上停留在一维水平，本文从生产实践中常用的中心回线法入手，基于电磁场本身的叠加原理，从麦克斯韦方程组出发，导出了中心回线瞬变电磁2.5维二次场（纯异常）的有限单元计算公式. 该算法采用三角形有限元网格，在尽可能拟合地下电性断面的情况下减少有限元网格的节点数和单元数；用选主元的LU分解法求解线性方程组，做到了在移动场源时只需改变右端项；在反傅氏变换中，使用新的波数选取方案，让波数m随时间t滑动. 最后给出的算例表明，该算法直接计算异常场，计算速度快、精度高.  相似文献   

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

DING Guoan  CHAN Chuenyu  GAO Zhiqiu  YAO Wenqing  LI Yoksheung  CHENG Xinghong  MENG Zhaoyang  YU Haiqing  WONG Kamhang  WANG Shufeng  MIAO Qiuju 《中国科学D辑(英文版)》2005,48(Z2)

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.  相似文献   

时间尺度重构EEMD-GRNN改进模型预测PM2.5的研究     

符海月  张祎婷 《地球信息科学学报》2019,21(7):1132-1142

合理构建PM_2.5浓度预测模型是科学、准确地预测PM_2.5浓度变化的关键。传统PM_2.5预测EEMD-GRNN模型具有较好的预测精度,但是存在过于关注研究数据本身而忽略其物理意义的不足。本研究基于南京市2014-2017年PM_2.5浓度时间序列数据,分析PM_2.5浓度多尺度变化特征及其对气象因子和大气污染因子的尺度响应,基于时间尺度重构进行EEMD-GRNN模型的改进与实证研究。南京市样本数据PM_2.5浓度变化表现为明显的天际尺度和月际尺度,从重构尺度（天际、月际）构建GRNN模型更具有现实意义;同时,PM_2.5对PM₁₀、NO₂、O₃、RH、MinT等因子存在多尺度响应效应,以其作为GRNN模型中的输入变量更具有时间序列上的解释意义。改进后的EEMD-GRNN模型具有更高的PM_2.5浓度预测精度,MAE、MAPE、RMSE和R²分别为6.17、18.41%、8.32和0.95,而传统EEMD-GRNN模型的模型有效性检验结果分别为8.37、27.56%、11.56、0.91。对于高浓度天（PM_2.5浓度大于100 μg/m³）的预测,改进模型更是全面优于传统EEMD-GRNN模型,MAPE为12.02%,相较于传统模型提高了9.03%。  相似文献   

相对湿度和PM_2.5浓度对大气能见度的影响研究:基于小时资料的多站对比分析          下载免费PDF全文

樊高峰  马浩  张小伟  刘樱 《Acta Meteorologica Sinica》2016,74(6):959-973

为了全面分析浙江省不同区域能见度变化基本特征及影响机理,基于杭州、宁波、温州3个国家基本气象站2013-2014年逐时能见度观测资料,比较分析了3市能见度变化的基本特征。发现3市不同等级能见度出现频率基本一致,随着能见度等级的提高,出现频率逐渐降低;从能见度的日变化来看,07时（北京时）前后最低,之后缓慢上升,14-15时达到最高,随后逐渐下降;全年有两个能见度较低时段,分别出现在12月-次年2月和5-6月;总体而言,宁波能见度最优,杭州和温州大体相当。功率谱分析结果表明,3市能见度均有显著的日周期,高频波段呈现出多个显著谱峰,低频波段存在若干显著谱峰。进一步开展机理分析,发现相对湿度和PM_2.5浓度是调制大气能见度的关键因子,相对湿度增大、PM_2.5浓度升高导致能见度降低。在同一相对湿度等级下,初始阶段能见度随PM_2.5浓度的升高迅速降低,到达“拐点”之后降低速率趋于缓慢。在同一PM_2.5浓度水平下,相对湿度越大,能见度越低,说明水汽对能见度也有重要影响。基于相对湿度和PM_2.5浓度两个因子,采用非线性拟合方案构建了大气能见度定量统计模型,总体而言模型拟合效果较好。最后针对研究中存在的不足和未来值得进一步发掘的科学问题进行了讨论。  相似文献   

2013年济南市大气能见度与相对湿度和PM10、PM2.5的关系     

吕建华  彭岩波  谢刚 《气象与环境科学》2016,39(4):93-97

对济南市2013年1—12月的能见度、相对湿度、PM10及PM2.5逐时监测数据分析,结果表明：能见度、相对湿度、PM10和PM2.5浓度有明显的月变化和日变化规律。在各项污染物中,能见度与颗粒物的相关性最高,与PM10的相关系数为-0.6718,与PM2.5的相关系数为-0.7422;在气象因子中,与相对湿度的相关性最高,相关系数为-0.6501。不同季节条件下,能见度与PM2.5的相关性明显优于PM10的,冬季能见度与颗粒物的相关性明显优于其他季节的。  相似文献   

精细反演计算在镇江五洲山磁异常再解释中的应用     

张作宏  魏邦顺  张大莲  等 《江苏地质》2016,40(4):653-661

江苏镇江五洲山地区存在多个磁异常,通过对该地区地质背景、地磁场特征的分析研究,结合数据处理技术对DC-19异常开展了二维小波多尺度分解、三维物性反演以及2.5维剖面反演等精细处理计算。结果表明,矿孔的深部、旁侧还存在较大规模的磁铁矿体,认为该地区具有较好的寻找矽卡岩型磁铁矿的前景。说明利用计算技术,通过精细反演可进一步深化对以往异常的认识,达到重新评价异常的目的。  相似文献   

钟姑地区典型矿床的重磁找矿模式     

汪启年  朱将波  郭信  周月  葛诚  时静  佟月 《安徽地质》2016,26(2):92-98

钟姑地区位于宁芜中生代火山岩盆地南段,已发现有白象山铁矿等多个大型铁矿,是长江中下游成矿带以玢岩型铁矿为主的矿集区。本文以钟姑地区实测岩石物性参数为桥梁,以实测重磁数据为基础,分析了该区白象山铁矿、钟九铁矿和云楼铁矿的重磁场分布特征,并根据典型矿区已知地质条件,运用成熟的2.5D重磁联合反演技术进行计算,从定量角度认识铁矿体深部发育形态、位置与重磁异常之间对应关系,建立钟姑地区白象山铁矿等典型矿床的重磁找矿模式,为该区进一步找矿突破提供地球物理场信息。  相似文献