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1.
城市群落大气污染源影响的空间结构及尺度特征 总被引：29，自引：1，他引：29
以迅速发展的城市群落-北京及周边区域为样本, 利用2003年冬季(2月)、夏季(8月)北京城市大气环境现场科学试验(BECAPEX, Beijing City Air Pollution Observation Experiment)建筑群边界层大气污染动力-化学过程观测资料以及相关的气象要素、卫星反演气溶胶光学厚度等综合资料, 进行“点-面”空间结构动力-统计合成分析, 剖析北京大城市及周边区域大气污染影响域的空间结构及多尺度特征. 结果表明, 冬、夏季不同污染排放源对大气污染成分特征的贡献率具有显著差异, 统计模型主成分分析结果亦表明, 冬季气溶胶颗粒物成分结构以SO2和NOx影响为主; 夏季粒子成分结构则以CO, NOx影响为主. 冬、夏季北京城区不同方位测点近地层大气动力、热力结构及建筑群上边界各类污染物种均具有“同位相”变化及其“影响域”空间尺度特征. 功率谱分析发现冬、夏季颗粒物浓度和大气风场动力结构的周期谱相吻合, 冬季以长周期为主, 夏季则多为短周期, 揭示出冬、夏季大气环流季节性尺度特征对大气污染变化周期特征的影响效应. 分析城市区域热力非均匀性特征, 可发现北京地区热岛多尺度效应与高层建筑群面积非均匀扩展特征存在相关关系. 城市大气动力、热力特征空间结构中城市边界层群筑群湍流尺度特征对城市大气污染多尺度特征具有重要影响. 晴空、稳定天气条件下MODIS气溶胶变分订正分析场和污染源追踪相关合成风矢场综合分析模型均表明, 冬季北京大气污染气溶胶颗粒物的排放源可远距离追溯到北京南部周边的河北、山东及天津等地更大尺度空间范围, 气溶胶指数高值区与北京及周边地区居民户数高值区(采暖面源)空间分布存在关联. 冬、夏季空气质点后向轨迹特征呈类似上述多尺度特征, 且描述出不同季节污染源空间分布的尺度特征差异, 城区大气污染周边源轨迹路径主体来自城市近郊固定工业面源或采暖面源, 且冬季周边污染源扩散输送距离较夏季呈更远的空间尺度, 上述结论描述出城市区域大气污染源影响和大气动力结构引起的多尺度空间影响域及季节性特征. 冬季TOMS气溶胶光学厚度高值区域位于北京地区并向南延伸, 且呈南北向带状分布, 可描述出周边地形分布对区域尺度大气污染源扩散的动力影响效应. 研究分析表明: 北京周边大地形“谷地”内冬季污染程度与南部周边地区的污染排放源密切相关; 北京及周边地区冬季的气溶胶光学厚度和日照时数的“反位相”变化特征显著, 冬季云量、雾日数与气溶胶呈区域尺度相关特征, 反映了该区域尺度气溶胶影响的局地气候效应. 另外, 流域面尺度的大气干、湿沉降分布对密云水库区域尺度空间水体的影响分析亦反映了夏季水、土、气多圈层污染源影响多尺度空间结构对密云水库水质影响的可能性. 相似文献
2.
EOF模型分析北京周边气溶胶影响域气候变化显著性特征 总被引：5，自引：0，他引：5
利用1979~2000年TOMS气溶胶光学厚度和华北地区气象站日照时数、雾日数、低云量等资料以及EOF模型综合统计分析方法,研究冬季北京及周边城市群落的气溶胶分布特征及其对区域气候的影响效应问题,重点探讨了北京周边区域气候EOF模型特征向量变化显著区与气溶胶影响效应的相关联系.分析多年平均冬季TOMS气溶胶光学厚度的区域分布,发现北京及其南部周边地区“马蹄型”大地形谷地内存在南北向带状大范围相对稳定的气溶胶浓度高值区空间分布;冬季气溶胶光学厚度在北京与周边地区存在高相关影响区,在此气溶胶相互影响显著区,冬季气溶胶光学厚度与雾日数、低云量呈年际变化“同位相”特征,表明特定区域大气环流背景下,北京及周边地区气溶胶变化对该地区低云量、雾日数的年际变化存在影响效应.进一步通过EOF模型特征分析,揭示出华北地区冬季日照时数减少、低云量和雾日数增多气候变化区及其长期演变趋势,尤其EOF模型第一特征向量中日照时数、雾日数及低云量变化显著区与其20世纪80~90年代偏差显著区近似重合,且这些变化特征显著区域均与北京周边南北向带状气溶胶光学厚度高值区及其高相关区呈对应关系;日照时数、雾日数、低云量EOF模型第一特征向量时间系数与区域平均气溶胶光学厚度年际变化呈“同位相”特征,且均呈长期演变上升趋势.EOF模型分析描述出北京南部周边地区冬季日照时数减少、低云量和雾日数增多的区域气候变化主体特征,揭示出区域气溶胶影响效应,即多年平均冬季气溶胶光学厚度高值区以及日照时数、低云量和雾日数EOF模型第一特征向量变化显著区均位于北京南部周边城市群落区域,上述相关分布特征揭示出北京南部周边城市群落影响域存在气溶胶气候效应区域性增强的变化趋势. 相似文献
3.
MODIS卫星遥感气溶胶产品在北京市大气污染研究中的应用 总被引：23，自引：0，他引：23
利用NASA MODIS气溶胶光学厚度产品与北京市空气污染指数做了长期比较分析, 发现二者的直接对比相关较低; 在引入季节变化的气溶胶标高、考虑了气溶胶的垂直分布后, 二者的相关系数有所提高; 在考虑了湿度影响因子订正后, 二者的相关系数显著提高. 证实卫星遥感气溶胶光学厚度在经过垂直和湿度影响两方面的订正后, 可以作为监测颗粒物污染物地面分布的一个有效手段. 利用 MODIS资料对2004年10月一次污染个例的分析, 表明卫星遥感气溶胶可以细致描绘地面污染事件的形成过程, 发现区域尺度输送和地形因素对北京市空气质量具有显著影响. 高分辨率的反演结果给出北京城区及周边地区气溶胶光学厚度的年平均分布, 表明高分辨率卫星遥感可能在监测颗粒物排放源分布上具有潜在的应用价值. 相似文献
4.
基于扫描差分光学吸收光谱（DOAS）系统,于2007年8月27日~9月4日期间对北京市朝阳区大气污染物SO2,HCHO,O3和NO2的垂直分布进行了连续监测,并对污染物垂直廓线进行了分析,详细探讨了SO2垂直分布特征以及夜间NO对O3的滴定作用.结果表明,SO2浓度通常没有明显垂直分层分布特征,但在清晨风速较低时呈现负梯度变化.研究发现夜间O3、NO和NO2之间存在稳态作用,表明城市区域O3的滴定主要来自于地面NO的直接排放,显示出NO的滴定作用对夜间O3、NO和NO2的垂直变化起到重要作用. 相似文献
5.
本文利用2013年6月至2015年10月北京南苑观象台两年多午后臭氧探空资料,初步分析了北京城区大气混合层内臭氧浓度的垂直分布规律以及典型天气条件下大气边界层臭氧的变化特征.主要结果有：（1）季节平均而言,地表至对流层中部（8 km）的臭氧浓度在夏季最高,冬季最低,相差50~130 μg·m-3,最大差异在边界层.总体而言,对流层臭氧浓度随高度有比较缓慢的增加,但是边界层内臭氧浓度的垂直结构随季节有比较大的差异：夏季混合层中部存在一个臭氧浓度极大值,这与夏季比较强的光化学生成臭氧有关;而在冬季地面臭氧浓度很低,平均值小于40 μg·m-3,说明冬季地面是臭氧很强的汇.（2）臭氧浓度季节内变率的季节差异也十分明显,夏季最大、冬季最小.季节内变率在从边界层向自由对流层过渡区域最小（夏季为24 μg·m-3,冬季仅为10 μg·m-3）,在边界层内变率较大,夏季可达64 μg·m-3（冬季为30 μg·m-3）,这也说明边界层化学过程明显影响臭氧浓度的变化.（3）我们从所有白天样本中严格筛选了部分混合层样本,并把臭氧浓度在由混合层向自由大气过渡时的垂直分布分成了三类,即臭氧浓度随高度增大（Ⅰ型）、减小（Ⅱ型）以及基本稳定不变（Ⅲ型）;臭氧垂直结构类型有明显的季节特征,夏季主要是Ⅱ型,而冬季则以Ⅰ型为主.（4）此外,我们还针对一些典型天气过程（强风、静稳雾天和PM2.5污染）边界层内臭氧的变化特征进行了分析,结果表明：强风切变产生的机械对流引起的充分混合,有利于高层臭氧向低层输送,使得混合层内臭氧浓度的垂直梯度明显减小,同时混合层高度较高,达3 km以上;在高湿度静稳天气控制下,大气混合层较稳定,对北京上空污染物的垂直扩散十分不利：颗粒物浓度升高,削弱到达近地层的太阳辐射,从而降低臭氧的生成效率,混合层内臭氧浓度与混合层厚度都处于较低水平. 相似文献
6.
北京地区SO_2污染的长期模拟及不同类型排放源影响的计算与评估 总被引：4，自引：0，他引：4
采用分行业、分季节、高分辨的北京市SO2排放源清单,和NCEP气象分析场资料,用HYSPLIT-4(HybridSingleParticleLagrangianIntegratedTrajectory)污染扩散模式,计算了北京2000年和2001年地面SO2逐日变化,分析了北京当地及周边地区不同类型排放源对北京地面SO2的影响.与实测值对比表明,模式能够较好的模拟出北京地面SO2的逐日变化特点和季节分布.计算的各种排放源对北京的影响说明,总体上,北京当地排放影响较大,周边源影响大约占20%左右,但在一定天气条件下,周边源贡献仍可超过30%以上,甚至个别时候超过40%;如果考虑周边源的采暖期源强增大一倍,则采暖期周边源平均贡献2000年和2001年分别增加到35%和40%.对北京市划分的7类排放源分别计算其对北京地面SO2的浓度贡献率发现,在北京市区的各类排放源中,占北京市区排放量较少部分(不到三分之一)的工业面源和锅炉面源对北京市区的SO2贡献很大,是北京市SO2污染治理的关键. 相似文献
7.
近年来,京津冀地区频繁发生O3和PM2.5同时超标的双高污染(CP)过程,给大气污染协同控制带来了严峻挑战.京津冀地区50%以上的CP事件发生在4～5月,并且在2018年达到了最高的11天. CP事件期间的O3和PM2.5浓度略低于但接近仅发生O3和PM2.5污染时的浓度,这表明双高污染会造成更为严重的危害.由斯堪的纳维亚遥相关型的两个中心与华北上空的异常反气旋环流中心组成的Rossby波波列导致京津冀地区出现高温、潮湿和静稳的气象条件,这同时增加了O3和PM2.5的浓度,有利于CP事件的发生.在2018年之后CP日数急剧减少,而气象条件并没有明显的趋势变化.因此,气象条件的变化并没有真正促成2019年和2020年CP日数的下降.这其中隐含着是PM2.5相关排放的减少导致了CP日数的减少(2019年和2020年共减少约11天).本文所揭示的不同污染事件之间大气条件的差异有助于在日-周的时间尺... 相似文献
8.
城市环境大气重污染过程周边源影响域 总被引：39，自引：9，他引：39
北京城市周边污染源影响问题是北京环境污染治理决策亟待解决的关键环节之一. 综合分析2001年1~3月份BECAPEX(Beijing City Atmospheric Pollution Experiment), MODIS (Moderate Resolution Imaging Spectroradiometer)与TOMS(Total Ozone Mapping Spectrometer)卫星遥感资料, 提出追踪污染源“上游”风场合成矢量法. 通过统计分析北京及周边地区TOMS与MODIS卫星遥感气溶胶区域性特征, 发现北京城市重污染过程与南部周边城市群落排放源影响相关显著, 北京周边向南开口的类似“马蹄型”地形可能导致周边源远距离输送的污染物“滞留”效应, 形成北京与南部周边排放源近似南-北向带状影响域. 综合分析北京地区重污染过程轨迹特征, 并选取2001年1~3月份重污染过程与空气质量良好时段作为分析样本, 采用HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory)轨迹模式进行模拟试验, 揭示了北京城区重污染过程河北、山东和天津等地城市群落污染排放源扩散轨迹. 选取北京城区异常重污染过程个例, 并用RAMS(Regional Atmosphere Model System)模式模拟试验, 亦揭示了北京城区异常污染过程周边外源贡献率, 进一步证实了北京城市重污染过程加剧的重要因素之一是南部周边城市污染物外源的输入. 相似文献
9.
为探索城市建设对局地及周边大气环境的影响,本文采用典型代表性天气条件,以北京主城区及其东部发展带小城镇群的发展变化为例,设计算例进行数值模拟.分析结果表明：城镇群建设发展通过地气的相互作用对局地环境产生显著影响,在本文选择的夏日晴好天气条件下,就1980～2004年城市区域布局状况,模拟域内北京城市用地增加19%,城市区域平均气温增加1.91℃,植被覆盖率减少20%,城市区域平均比湿减少3.3 g·kg-1,并且城市发展的格局规模不同,对城市气象环境的影响程度也不同. 此外,由于地气多因子的相互影响和反馈作用,城建规模的变化对周边的环境也存在显著的影响,城建规模越大,对周边的影响越大．例如, (1) 北京主城区的存在对周边小城镇午间14:00近地面温度影响最大可达到1.2℃,混合层高度可增高150 m左右; (2) 城市建设在影响周边气象环境的同时,也改变了城市污染物的输送扩散能力,北京主城区的存在使周边小城镇PM10的允许排放总量减小18.02 t·d-1,同时,随着周边小城镇城市规模的扩大,影响主城区PM10逐渐由净的输出转变为净的收入,小城镇群的存在对主城区PM10净收支的贡献率达到0.192 t·d-1. 相似文献
10.
本文利用区域气候模式RIEMS2.0(Regional Integrated Environmental Model System)和2006年以及2020年三种排放情景下的排放资料,研究了2006年气候背景下的人为气溶胶的浓度分布特征及辐射效应,估算了未来不同排放情景下人为气溶胶的主要成分硫酸盐、硝酸盐、黑碳、有机碳(含二次有机碳)的综合气候效应.结果表明:(1)2006年中国地区人为气溶胶浓度硫酸盐>有机碳>硝酸盐>黑碳,其区域柱浓度平均值分别为6.0、4.0、1.3和0.3 mg/m2.(2)2006年硫酸盐、硝酸盐、有机碳和黑碳的平均辐射强迫分别为-1.32、-0.60、-0.40和0.28 W/m2.硫酸盐、硝酸盐和有机碳的负辐射强迫超过黑碳的正辐射强迫,人为气溶胶总辐射强迫为-1.96 W/m2.(3)人为气溶胶的辐射效应及引起的地面气温变化对排放源非常敏感,未来采取不同排放政策导致的人为气溶胶的含量及辐射效应有较大差异.在未来排放增加的情景下,各区域的气溶胶浓度、辐射强迫、气温下降幅度和降水减少幅度也相应加大. 相似文献
11.
Spatial structure and scale feature of the atmospheric pollution source impact of city agglomeration 总被引：1，自引：0，他引：1
The spatial structure and multi-scale feature of the atmospheric pollution influence domain of Beijing and its peripheral areas (a rapidly developed city agglomeration) is dissected and analyzed in this paper on the basis of the atmospheric pollution dynamic-chemical process observation data of the urban building ensemble boundary layer of the Beijing City Air Pollution Observation Experiment (BECAPEX) in winter (February) and summer (August) 2003, and relevant meteorological elements and satellite retrieval aerosol optical depth (AOD), etc. comprehensive data with the dynamic-statistical integrated analysis of "point-surface" spatial structure. Results show that there existed significant difference in the contribution of winter/summer different pollution emission sources to the component character of atmospheric pollution, and the principal component analysis (PCA) results of statistical model also indicate that SO2 and NOX dominated in the component structure of winter aerosol particle; instead, CO and NOX dominated in summer. Surface layer atmospheric dynamic and thermal structures and various pollutant species at the upper boundary of building ensembles at urban different observational sites of Beijing in winter and summer showed an "in-phase" variation and its spatial scale feature of "influence domain". The power spectrum analysis (PSA) shows that the period spectrum of winter/summer particle concentration accorded with those of atmospheric wind field: the longer period was dominative in winter, but the shorter period in summer, revealing the impact of the seasonal scale feature of winter/summer atmospheric general circulation on the period of atmospheric pollution variations. It is found that from analyzing urban area thermal heterogeneity that the multiscale effect of Beijing region urban heat island (UHI) was associated with the heterogeneous expansion of tall buildings area. In urban atmospheric dynamical and thermal characteristic spatial structures, the turbulent scale feature of the urban boundary layer (UBL) of architectural complexes had important impact on the multi-scale feature of urban atmospheric pollution. The comprehensive analyses of the variational analysis field of Moderate Resolution Imaging Spectroradiometer (MODIS) AOD-surface PM10 under the condition of clear sky and the correlation resultant wind vector field for pollution source-tracing suggest that the emission sources for winter Beijing atmospheric pollution aerosols particle might be remotely traced to the south peripheral greater-scale spatial range of Hebei, Shandong, Tianjin, etc., and the spatial distribution of the high value area of AOD was associated with that of the high value area of resident family number (heating surface source). The backward trajectory feature of winter/ summer air particles exhibits analogous multi-scale feature, and depicts the difference in the scale feature of the pollution sources spatial distribution in different seasons. The peripheral source trajectory paths of urban atmospheric pollution (UAP) mainly come from the fixed industrial surface source or heating surface source in the outskirt of Beijing, and the diffusion and transport distance of peripheral sources in winter is larger than one in summer. The above conclusions depict the multi-scale spatial influence domain and seasonal features caused by UAP source influence and atmospheric dynamical structure. The high value area of the winter Total Ozone Mapping Spectrometer (TOMS) AOD lay in the Beijing region and its south peripheral area, an S-N zonal pattern, which reflects the dynamical effect of peripheral topographic pattern on the diffusion of regional scale atmospheric pollution sources. Study suggests that the extent of winter atmospheric pollution within the "valley" megarelief in Beijing and periphery was close related with the pollution emission sources of the south peripheral area; and the significant "anti-phase" variation feature of winter AOD and sunshine duration in Beijing and its peripheral areas, and regional scale correlation of low cloud cover, fog days, and aerosols reflects the local climatic effect of aerosol influence in this region. Besides, analysis of the impacts of atmospheric dry/wet deposition distributions within a valley-scale on the regional water body of Miyun reservoir also reveals the possible influence of the multi-scale spatial structure of summer water, soil and atmospheric pollution sources on the water quality of Miyun reservoir. 相似文献
12.
Using the total ozone mapping spectrometer (TOMS) aerosol optical depth (AOD)data and the sunshine duration, fog days, Iow cloud cover (LCC), etc. meteorological data in 1979-2000 in North China, as well as empirical orthogonal function (EOF) mode statistical analyses method, the winter aerosol distributive character of Beijing and peripheral city agglomeration and its influence effect on regional climate are investigated in this paper, especially the relation between aerosol influence effect and distinct change regions of eigenvectors of EOF mode. It is found from analyzing the regional distribution of the long-term averaged winter TOMS AOD that there is a large-scale relatively stable high value zone of aerosol concentration in the valley of the Beijing and peripheral U-shape megarelief. A high correlation area of AOD between Beijing and its southern peripheral exists in winter, and in this significant region of aerosol interaction, there is "in-phase" character of the interannual variations of winter AOD, fog days, and LCCs. It indicates that the variations of aerosol in Beijing and its peripheral areas have impacts on interannual changes of fog days and LCCs in this area. The EOF analyses of the meteorological data further reveal the climate change regions and long-term trends of winter sunshine duration-reducing, and LCC- and fog days-increasing in North China. The areas of significant changes of the first EOF eigenvectors (FEE) of sunshine duration, fog days, LCCs almost superpose on corresponding marked regions of interdecadal differences between the 1990s and 1980s, and all accord with the S-N zonal high value pattern and high correlation region of winter AOD in Beijing and its peripheral areas. Interannual variations of their associated time coefficients (ATC) are in phase with that of regional mean AOD, and both of them have a secular rising trend. Results by EOF mode analyses depict the regional climatic change principal character of winter sunshine duration-reducing, and LCC- and fog days-increasing in peripheral areas to the south of Beijing, and reveal the regional influence effect of aerosol, i.e. the high value zone of long-term averaged winter AOD, significant change regions of FEE of sunshine duration, fog days, and LCC all lie in peripheral city agglomeration to the south of Beijing. These distributive features above suggest that there exists a regional strengthening trend of aerosol climatic effect within influence domain in peripheral city agglomeration to the south of Beijing. 相似文献
13.
VIIRS(Visible Infrared Imaging Radiometer Suite)作为MODIS(The MODerate resolution Imaging Spectroradiometer)的后继传感器,可在全球范围内实现对气溶胶的连续时空监测.卫星反演的气溶胶光学厚度(Aerosol Optical Depth,AOD)是研究地球能量收支平衡、气候效应和空气质量的重要大气参数.但在中国重污染天气情况下,现有的VIIRS陆地气溶胶产品存在一定不足.因此,本研究改进云识别方法,优化像元筛选,约束气溶胶类型选择,实现重污染情况下AOD的反演.基于地基AERONET(AErosol RObotic NETwork)的验证结果表明,相比NOAA(National Oceanic and Atmospheric Administration)产品,改进后的反演结果克服了反演值偏低的问题,且表现出更好的相关性,RMSE从0.236下降到0.219.为验证在重污染条件下改进算法的适用性和准确性,本文对比了两种污染条件下的反演结果(0.61).统计结果表明,在较重污染天气条件下(AODAERONET>1),相比NOAA的AOD产品,本文结果的反演率从32.3%提升为68.8%,回归分析的斜率提高为0.80,相关系数达到0.76,均方根误差为0.307,在增加反演量的同时保证了反演的精度. 相似文献
14.
基于2015—2017年北京闪电定位网(BLNET)总闪资料与35个自动空气质量监测站PM2.5数据,分析了北京地区(39.5°N—41.0°N,115.0°E—117.5°E)夏季(6—8月)闪电活动与PM2.5的时空分布特征,同时针对117次雷暴天气,探讨了气溶胶浓度变化对闪电活动的可能影响.结果表明:PM2.5浓度及总闪密度均呈现自西北向东南升高的空间分布特征.闪电峰值在污染背景下出现的时间(19∶00LT)晚于清洁背景下(15∶00LT)约4h,且总闪百分比(～20%)可达清洁背景下(～9%)的两倍.对雷暴前1～4h的PM2.5浓度与时间窗(12∶00—22∶00LT)内总闪数目的中位数进行相关分析,发现PM2.5浓度低于130μg·m-3时,PM2.5与总闪数存在明显正相关,此时气溶胶可能通过影响云微物理过程进而影响雷暴的对流发展,增强闪电活动;PM2.5大于150μg·m-3时,总闪数随PM2.5浓度的增加呈减少趋势,可能的原因是高气溶胶浓度下地面太阳辐射显著下降,对流活动受到抑制,导致闪电活动减少.当PM2.5浓度在130～150μg·m-3时,两者关系不明显. 相似文献
15.
Influencing domain of peripheral sources in the urban heavy pollution process of Beijing 总被引：1，自引：0，他引：1
Multiple cities in a diveloped economic area may consist of a city cluster,and the difusion and mixing of its pollutants result in the effect of pollutants plume between cities and the large-scale regional pollution diffusion phenomenon.The distant transfer and diffusion of pollutants occurs when massive aerosols are affected by the dynamic porcess of large-scale circulations.Research suggesten that the life span of aerosol particles whose diameters are about 1 um is the longest.The longevity … 相似文献
16.
LI Chengcai MAO Jietai Alexis K. H. Lau YUAN Zibing WANG Meihua LIU Xiaoyang 《中国科学D辑(英文版)》2005,48(Z2)
The direct correlation between NASA MODIS aerosol optical depth (AOD) products and the air pollution index (API) in Beijing was found relatively low based on the long-term comparison analysis. The correlation improved to some extent after taking account of the seasonal variation of scale height and the vertical distribution of aerosols. The correlation coefficient further improved significantly after considering the influencing factor of Relative Humidity (RH). This study concluded that satellite remote-sensing could serve as an efficient tool for monitoring the spatial distribution of particulate pollutants on the ground-level, as long as corrections have been made in the two aforementioned processes. Taking advantage of the MODIS information, we analyzed a pollution episode occurring in October 2004 in Beijing. It indicated that satellite remote-sensing could describe the formation process of the ground-level pollution episode in detail, and showed that regional transport and the topography were crucial factors to air quality in Beijing. The annual averaged distribution in the urban area of Beijing and its surroundings could be also obtained from the high-resolution retrieval results, implicating that high-resolution satellite remote-sensing might be potential in monitoring the source distribution of particulate pollutants. 相似文献
17.
根据北京塔7层涡动系统2012年5月至2013年12月的湍流观测数据,分析了北京城区二氧化碳浓度在不同高度层次的日变化和月变化特征,并初步给出不同季节和日变化时间段内二氧化碳的浓度垂直廓线.结果表明:二氧化碳浓度整体随高度而下降;各观测层均有浓度的明显日变化,夏季最为明显,冬季相对平缓;近地层浓度直接受城市供暖、地表植被、交通运输等碳源影响,更高观测层浓度则受对流输送和天气过程影响较大;垂直方向上,冬季浓度变化范围最大,夏季层间浓度变化最明显;在一天中的任何时刻,近地面层二氧化碳浓度的日变化最低值一般出现在夏季,50m以上则出现在春季,浓度最高值总是出现在冬季;根据对二氧化碳浓度四季垂直廓线变化的分析可以看出,边界层二氧化碳浓度强烈受到碳源、下垫面植被、大气稳定度、环境温度和天气过程等因素的影响. 相似文献
18.
Beijing often suffers under heavy smog.During such events which occur mostly in autumn and winter,people are desperate for fresh air.The formation of heavy smog is due to foremost human induced air pollution,but geographic and meteorological conditions,especially below a surface inversion,play an important role.We propose to destroy the inversion by pumping air from above the inversion layer to the surface layer to alleviate the severity of the smog.While long-term air quality improvement depends on the reduction of air pollution emission,air pumping may provide relief in the interim for the Beijing citizens.We estimate that an air pumping at a rate 2×10~7m~3s~(–1)can lead to significantly improved air quality in Beijing,due to(1)direct clean air input;(2)increased instability and vertical mixing and(3)a positive radiation-mixing feedback.The pumping requires an energy input of 10 GW,comparable with the energy consumption in Beijing for air conditioning in summer.We propose to use wind energy from Inner Mongolia for the pumping,which has currently an installed wind energy capacity of 70GW. 相似文献
19.
HUANG XiaoFeng YUN Hui GONG ZhaoHeng LI Xiang HE LingYan ZHANG YuanHang HU Min 《中国科学:地球科学(英文版)》2014,57(6):1352-1362
PM2.5 is the key pollutant in atmospheric pollution in China.With new national air quality standards taking effect,PM2.5 has become a major issue for future pollution control.To effectively prevent and control PM2.5,its emission sources must be precisely and thoroughly understood.However,there are few publications reporting comprehensive and systematic results of PM2.5 source apportionment in the country.Based on PM2.5 sampling during 2009 in Shenzhen and follow-up investigation,positive matrix factorization(PMF)analysis has been carried out to understand the major sources and their temporal and spatial variations.The results show that in urban Shenzhen(University Town site),annual mean PM2.5 concentration was 42.2μg m?3,with secondary sulfate,vehicular emission,biomass burning and secondary nitrate as major sources;these contributed30.0%,26.9%,9.8%and 9.3%to total PM2.5,respectively.Other sources included high chloride,heavy oil combustion,sea salt,dust and the metallurgical industry,with contributions between 2%–4%.Spatiotemporal variations of various sources show that vehicular emission was mainly a local source,whereas secondary sulfate and biomass burning were mostly regional.Secondary nitrate had both local and regional sources.Identification of secondary organic aerosol(SOA)has always been difficult in aerosol source apportionment.In this study,the PMF model and organic carbon/elemental carbon(OC/EC)ratio method were combined to estimate SOA in PM2.5.The results show that in urban Shenzhen,annual SOA mass concentration was 7.5μg m?3,accounting for 57%of total organic matter,with precursors emitted from vehicles as the major source.This work can serve as a case study for further in-depth research on PM2.5 pollution and source apportionment in China. 相似文献