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1.
为探究地面气溶胶质量浓度遥感反演模型在年际及区域尺度上的适用性,确定一种可以在区域尺度上业务运行的反演模型,基于2015-2016年河南省28个城市MODIS气溶胶光学厚度、PM_(2.5)质量浓度、地面气象观测能见度和相对湿度,分别采用半经验模型和非线性多元回归模型建立了分季节反演模型,并基于2017年观测数据对两种模型的精度进行了对比评价。结果表明:半经验模型中标高订正的AOD与经过湿度订正的PM_(2.5)质量浓度建立反演模型效果最好,四个季节反演模型决定系数R~2分别为0.3938、0.3507、0.3488及0.4212。非线性多元回归模型最优组合为AOD、气溶胶波长指数、气溶胶标高与相对湿度,四个季节反演模型决定系数R~2分别为0.4295、0.3598、0.4099和0.5616。两种反演模型验证结果均通过0.001的显著性检验,非线性多元回归模型的验证决定系数大于半经验模型的,春季和冬季非线性多元回归模型的验证斜率更接近1,而夏季和秋季半经验模型验证斜率更接近1。非线性多元回归模型建模及验证相关性更高,且可有效避免高相对湿度条件下异常值的出现,业务适用性更好。  相似文献   

2.
利用MODIS资料监测京津冀地区近地面PM2.5方法研究   总被引：7，自引：0，他引：7  
为建立京津冀地区冬季近地面细颗粒物浓度监测方法模型,利用气象模式资料对2013年1-3月MODIS的AOD二级深蓝算法产品进行湿度和垂直订正,与同期观测的地面细颗粒物PM2.5资料进行相关分析。结果表明：AQUA的MODIS深蓝算法AOD产品更适用于建立冬季AOD-PM2.5遥感监测模型,其R2为0.33;以气象模式资料中边界层高度代替气溶胶标高对MODIS的AOD进行垂直订正,并结合IMPROVE观测的气溶胶吸湿增长特征构建分区湿度订正方法,可以提高AOD-PM2.5模型结果的精度,建立较为理想的京津冀地区冬季遥感反演综合模型,模型结果与地面监测结果R2达0.5以上。根据建立的模型计算了2013年1-3月的京津冀地区PM2.5月平均浓度,京津冀地区1月的PM2.5浓度较高,南部大部分地区空气质量已经达到重度污染水平。  相似文献   

3.
本文利用2014年全年北京市12个空气质量监测站的逐小时PM_(2.5)地面观测资料,以及Terra卫星和Aqua卫星的MODIS 3 km气溶胶光学厚度(AOD)产品,分析了地面PM_(2.5)和两颗卫星AOD的时空分布特征,并在时空匹配的基础上,建立了AOD与PM_(2.5)浓度之间的回归模型。结果表明:PM_(2.5)浓度在城区高、郊区低,最低值位于定陵站,城区站和郊区站的逐时PM_(2.5)浓度的日变化分别呈"双峰型"和"单峰型";两颗卫星AOD数值也均是城区高、郊区低,沿山区的边界有明显的AOD梯度,且城区上午Terra卫星的AOD高于下午Aqua卫星的AOD,而郊区上、下午的AOD基本相同;Aqua卫星AOD与PM_(2.5)的确定系数(R2)较Terra卫星AOD与PM_(2.5)的确定系数平均高0.11,且城区站点两颗卫星AOD与PM_(2.5)相关性均较郊区站点AOD与PM_(2.5)相关性偏高;综合来看,Aqua卫星的AOD与城区的PM_(2.5)相关系数最高,即Aqua卫星的AOD更适于监测和反演城区地面的PM_(2.5)。  相似文献   

4.
利用2014—2016年西安、咸阳、宝鸡、渭南、铜川的逐日PM_(10)质量浓度和同期美国国家航空航天局(NASA)的MODIS气溶胶产品(3 km),提取有效的气溶胶光学厚度(AOD)数据并进行标高及湿度订正,得到近地面"干"消光系数(AODSEC-RH),分析关中及5个地市PM_(10)质量浓度、AOD、AODSEC-RH的月、季、年时空变化特征。结果显示:近3 a关中及5个地市PM_(10)质量浓度均呈递减趋势;1月为峰值,7月为谷值,全年呈波动变化,冬季最大;3月较厚的逆温层及较稳定的大气致使污染不易扩散,PM_(10)质量浓度下降缓慢;4—5月降水开始增多,PM_(10)质量浓度下降较快;夏季PM_(10)质量浓度最低;10月雾和霾天气活跃,PM_(10)质量浓度迅速回升。西安年平均PM_(10)质量浓度较其他4市偏高,关中四季的PM_(10)质量浓度高值区均位于西安、咸阳、渭南市。近3 a关中整体AOD有所下降,高值区也位于西安、咸阳、渭南。夏季高温高湿,气溶胶吸湿强,AOD最大;其次为春季,气温回升、空气干燥、植被稀少,大风为沙尘天气提供了充分的动力,AOD次高;秋冬季AOD整体偏小。经标高及湿度订正的AODSEC-RH夏季明显降低,冬季明显升高,时空变化特征更接近于PM_(10)质量浓度,能充分体现近地面污染特征。  相似文献   

5.
利用MODIS气溶胶光学厚度(AOD,Aerosol Optical Depth)产品与同期乌鲁木齐市空气质量指数进行相关性分析,得到二者的相关系数为0.664。对MODIS AOD产品进行垂直和湿度订正后,二者的相关性显著提高,相关系数从0.664提高到0.805。订正后按季节分类统计,春、夏、秋3季的相关系数分别为0.775、0.608和0.822,其中秋季的订正更为有效,可用性更高。这可能受到不同季节气溶胶来源、特征以及数据样本差异的影响。最后分别建立全年、春季、夏季和秋季的线性、对数、一元二次、乘幂和指数5种类型的拟合模型。考虑模型易于利用的因素,依据各拟合模型相关系数的大小得到全年以及各季节最优拟合模型,该模型函数可用来反演和监测乌鲁木齐市空气质量指数。  相似文献   

6.
根据河北邢台市2015年10月11—23日一次重污染天气过程的激光雷达探测数据,对大气污染物浓度和雷达反演得出的大气边界层(PBL)高度、气溶胶光学厚度(AOD)和消光系数的变化进行分析。结果表明:在剔除降水因子的影响后,PBL高度对PM_(2.5)浓度有显著影响,PBL高度越低,PM_(2.5)浓度越高,且两者的相关性夜间好于日间;大气污染物浓度的增加会导致AOD和气溶胶消光系数的显著升高,且AOD与PM_(2.5)浓度的相关性日间好于夜间,在降水的湿沉降效应和大气相对湿度增加的影响下,会出现大气污染物浓度下降,但AOD升高的现象;300 m高度的气溶胶消光系数与地面污染物浓度的日变化趋势较为一致,贴近地面处消光系数相对较小。整体而言,随着PBL高度下降、AOD上升和消光系数增加,环境大气质量逐步趋于恶化。  相似文献   

7.
选取贵阳市环保站2013年3月—2014年2月共12个月的主要污染物(PM_(10)、PM_(2.5)和O_3)浓度的小时均值进行分析,发现PM_(10)和PM_(2.5)在20时—次日08时较容易出现日最大值,O_3在12—18时较容易出现日最大值,PM_(10)和PM_(2.5)污染物浓度的月平均,以夏季最低,冬春两季最高,这可能与贵阳市冬春两季的采暖有一定的关系。而O_3浓度的月平均值以冬夏两季较低,春秋两季较高,但整体变化幅度不大。分析以上3种污染物和气象要素的相关性发现,湿度对污染物浓度较大,呈负相关。运用逐步回归方法分别建立PM_(10)、PM_(2.5)和O_3的预报方程,其中PM_(10)的预报方程预报等级的准确率为67.81%,订正后准确率为70.55%;PM_(2.5)的预报方程准确率为65.75%,订正后准确率为71.23%,故业务对PM_(10)和PM_(2.5)的预报中可以参考订正值。O_3的预报方程准确率为70.55%,订正后准确率为68.49%,业务中预报O_3可以直接参考预报值。  相似文献   

8.
京津冀地区气溶胶光学厚度反演及其空间分布特征   总被引：1，自引：0，他引：1  
利用2014年9月1日至2015年5月31日Terra/MODIS MOD 021KM数据,以京津冀地区为研究区域,采用深蓝算法和查找表法反演京津冀地区1 km分辨率的气溶胶光学厚度,并将反演的气溶胶光学厚度与NASA产品和CE-318观测的气溶胶光学厚度进行比较。结果表明:反演的气溶胶光学厚度与NASA MOD 04_L2(10 km×10 km)和MOD 04_3K(3 km×3 km)两种气溶胶产品的空间分布具有高度的一致性,且空间分辨率更高;反演的气溶胶光学厚度与石家庄站CE-318观测气溶胶光学厚度的平均绝对误差为0.07左右,二者之间的相关系数R~2=0.956。卫星过境时,1 km反演的气溶胶光学厚度与MOD 04_L2气溶胶产品的平均误差约为0.06,反演的气溶胶光学厚度与MOD 04_3K气溶胶产品的平均误差约为0.03。对反演的气溶胶光学厚度与河北省PM_(2.5)和PM_(10)质量浓度的空间分布进行相关性分析表明,气溶胶光学厚度AOD与PM_(2.5)和PM_(10)质量浓度的相关系数分别为0.745、0.663,说明1 km反演的AOD可以有效反映区域PM_(2.5)和PM_(10)质量浓度的空间分布。  相似文献   

9.
北京地区PM10浓度空间分布特征的综合变分分析   总被引：7，自引：0，他引：7       下载免费PDF全文
利用2003年10月北京地区PM10浓度流动观测资料和同期MODIS AOD(Aerosol Optical Depth)高分辨率遥感资料，采用卫星遥感地面观测变分订正处理方法，综合分析了北京地区PM10浓度的空间分布特征以及机动车排放的影响效应。动态观测试验结果表明:北京城区大部分为轻污染区, 北京近郊区PM10浓度高值区沿环路呈环状分布，其中北京西南部、南部和东北部污染较严重，北京城郊街区PM10的空间分布受机动车排放的影响较大。MODIS卫星遥感资料分析表明:北京城区及近郊区AOD值较远郊区高得多，AOD空间分布场中存在虚假高值区，AOD非均匀分布特征不明显。采取点面结合综合观测研究思路，运用卫星遥感地面观测综合变分分析方法，可以取得客观订正的显著效果。经地面实测PM10浓度变分订正后的AOD变分场可以较高分辨率信息描述北京地区AOD的非均匀分布特征，弥补地面PM10浓度观测的缺陷。  相似文献   

10.
以北京为研究区域,利用MODIS气溶胶光学厚度产品AOT(Aerosol Optical Thickness)定量反演北京近地面PM2.5质量浓度。首先对MODIS AOT与对应地面实测PM2.5质量浓度为数据源,两者的线性相关系数为0.323,经过AOT标高订正和PM2.5湿度订正后,两者相关系数升高为0.467;进一步分析AOT与PM2.5的季节变化特征发现,秋季相关性最高(0.802),春季最低(0.252),其他季节介于之间,并深入分析了AOT与PM2.5自身物理化学特性及气象因子对两者相关性的影响机制;最后在耦合标高和湿度订正基础上,建立了一个近地面PM2.5质量浓度对数反演模型,并与地面实测PM2.5样本进行对比分析,结果显示均方根误差为2.84%,平均误差为9.53%,验证了该对数反演模型能较好的依据AOT反演近地面PM2.5质量浓度的可行性,为卫星遥感高精度定量反演PM2.5提供了科学依据。  相似文献   

11.
We used simultaneous measurements of surface PM2.5 concentration and vertical profiles of aerosol concentration, temperature, and humidity, together with regional air quality model simulations, to study an episode of aerosol pollution in Beijing from 15 to 19 November 2016. The potential effects of easterly and southerly winds on the surface concentrations and vertical profiles of the PM2.5 pollution were investigated. Favorable easterly winds produced strong upward motion and were able to transport the PM2.5 pollution at the surface to the upper levels of the atmosphere. The amount of surface PM2.5 pollution transported by the easterly winds was determined by the strength and height of the upward motion produced by the easterly winds and the initial height of the upward wind. A greater amount of PM2.5 pollution was transported to upper levels of the atmosphere by upward winds with a lower initial height. The pollutants were diluted by easterly winds from clean ocean air masses. The inversion layer was destroyed by the easterly winds and the surface pollutants and warm air masses were then lifted to the upper levels of the atmosphere, where they re-established a multi-layer inversion. This region of inversion was strengthened by the southerly winds, increasing the severity of pollution. A vortex was produced by southerly winds that led to the convergence of air along the Taihang Mountains. Pollutants were transported from southern–central Hebei Province to Beijing in the boundary layer. Warm advection associated with the southerly winds intensified the inversion produced by the easterly winds and a more stable boundary layer was formed. The layer with high PM2.5 concentration became dee-per with persistent southerly winds of a certain depth. The polluted air masses then rose over the northern Taihang Mountains to the northern mountainous regions of Hebei Province.  相似文献   

12.
面对日益严峻的大气污染形势,针对卫星气溶胶光学厚度（AOD）资料在灰霾数值预报领域的合理有效利用问题,使用WRF-Chem（WRF coupled with Chemistry）大气化学模式以及GSI（Gridpoint Statistical Interpolation）三维变分同化系统,利用MODIS和FY-3A/MERSI AOD资料,对一次灰霾天气过程进行了同化预报试验。试验结果显示,同化卫星AOD资料有效改善了模式初始场,MODIS和MERSI同化试验分别在AOD分析场的中心强度和空间分布各具优势,且对PM2.5和PM10的后续预报改进明显;从统计分析上看,同化试验的预报效果整体上好于控制试验,同化试验中PM2.5和PM10预报值的平均值、中值、平均偏差、均方根误差等指标均明显优于控制试验,且MODIS和MERSI同化试验分别在PM2.5和PM10预报统计结果中体现出了优势;卫星AOD资料同化能明显降低污染事件的空报率和漏报率,提高预报的TS评分和ETS评分。不同卫星AOD资料的差异对分析场中AOD的分布和强度产生了相应影响,进而影响了模式的灰霾预报效果;本次试验中,MODIS和MERSI AOD同化试验分别在PM2.5和PM10预报的评分上表现更佳。结果表明,卫星AOD资料同化对数值预报产生了积极的效果。   相似文献   

13.
利用无人机搭载气象及环境监测设备于2020年7月29—31日在太原进行飞行试验,对不同高度层颗粒物和气象要素进行观测,得到PM_(2.5)三维分布及其随时间的变化特征,并通过气象要素、天气形势和后向轨迹分析得到污染累积和消散成因以及外地传输作用影响。结果表明:PM_(2.5)浓度的垂直分布差异显著,下午大部分时次满足"下高上低"规律,上午边界层垂直混合和颗粒物吸湿增长可能导致"下低上高"的情况;逆温层对大气垂直混合有明显抑制作用;29日为污染物积累过程,30日和31日白天均为消散过程;副热带高压带来的小风、高湿环境是29日颗粒物逐渐累积的原因,30日槽前对流发展和较大的风速有利于颗粒物浓度下降,31日相对湿度较低、对流发展旺盛使PM_(2.5)浓度快速下降;试验期间气流主要来自东南方向,太原市PM_(2.5)本地积累占主导地位,外地传输更多来自于本省晋中、长治等邻近城市。  相似文献   

14.
Based on observations of urban mass concentration of fine particulate matter smaller than 2.5 μm in diameter (PM2.5), ground meteorological data, vertical measurements of winds, temperature, and relative humidity (RH), and ECMWF reanalysis data, the major changes in the vertical structures of meteorological factors in the boundary layer (BL) during the heavy aerosol pollution episodes (HPEs) that occurred in winter 2016 in the urban Beijing area were analyzed. The HPEs are divided into two stages: the transport of pollutants under prevailing southerly winds, known as the transport stage (TS), and the PM2.5 explosive growth and pollution accumulation period characterized by a temperature inversion with low winds and high RH in the lower BL, known as the cumulative stage (CS). During the TS, a surface high lies south of Beijing, and pollutants are transported northwards. During the CS, a stable BL forms and is characterized by weak winds, temperature inversion, and moisture accumulation. Stable atmospheric stratification featured with light/calm winds and accumulated moisture (RH > 80%) below 250 m at the beginning of the CS is closely associated with the inversion, which is strengthened by the considerable decrease in near-surface air temperature due to the interaction between aerosols and radiation after the aerosol pollution occurs. A significant increase in the PLAM (Parameter Linking Aerosol Pollution and Meteorological Elements) index is found, which is linearly related to PM mass change. During the first 10 h of the CS, the more stable BL contributes approximately 84% of the explosive growth of PM2.5 mass. Additional accumulated near-surface moisture caused by the ground temperature decrease, weak turbulent diffusion, low BL height, and inhibited vertical mixing of water vapor is conducive to the secondary aerosol formation through chemical reactions, including liquid phase and heterogeneous reactions, which further increases the PM2.5 concentration levels. The contribution of these reaction mechanisms to the explosive growth of PM2.5 mass during the early CS and subsequent pollution accumulation requires further investigation.  相似文献   

15.
侯梦玲  王宏  赵天良  车慧正 《大气科学》2017,41(6):1177-1190
本文利用GRAPES_CUACE大气化学模式对京津冀地区2015年12月重度雾霾过程进行了模拟和评估。京津冀地区能见度和PM2.5模拟值与观测值的对比表明:该模式能较好地模拟京津冀地区能见度和PM2.5的逐日变化情况,但模式存在对伴随着重污染发生的低能见度模拟偏高的问题。以12月5~10日的重度雾霾过程为重点,针对地面风速、边界层高度、相对湿度、PM2.5及其对能见度的影响进行了详细分析,研究结果表明:污染过程中大部分地区过程平均风速低于2 m s-1,边界层平均高度低于600 m,相对湿度较高。模式低能见度模拟偏高可能因为:（1）模式模拟重雾霾时段的PM2.5极大值浓度偏低。（2）模拟相对湿度存在系统性偏低的误差,这一误差对能见度的影响表现为两方面,一是相对湿度会通过影响可溶性气溶胶的吸湿增长过程影响气溶胶质量浓度,导致气溶胶消光系数的计算偏低;二是目前模式中采用的能见度的参数化公式考虑了相对湿度对气溶胶吸湿增长的影响,没有考虑雾滴的直接消光作用。  相似文献   

16.
The size-segregated chemical composition of aerosol particles was investigated during 1?year at the puy de D?me (1,465?m?a.s.l.), France. These measurements aimed to a better understanding of the influence of the air mass origin on the size-segregated chemical composition of the aerosol at an altitude site. Mountain site measurements are important because they are representative of long range transport and useful for model validation. PM1 mass concentration exhibits a seasonal variability with a summer maximum. The composition of PM1 did not change significantly in terms of relative contribution of water soluble inorganic ions but is rather variable in term of total mass concentrations. For the PM10-1, a different seasonal behaviour was found with maxima concentrations in autumn-winter. Aerosols were classified into four different categories according to their air mass origin: marine, marine modified, continental and Mediterranean. The PM10 aerosol mass at 50?% relative humidity was close to 2.5???g?m?3 in the marine, 4.3???g?m?3 in the marine modified, 10.3???g?m?3 in the continental and 7.7???g?m?3 in the Mediterranean sectors. We noted that the influence of the air mass origin (on the chemical properties) could be seen especially on the PM10-1. A significant PM10-1 mode was found in marine, modified marine, and Mediterranean air masses, and PM1 dominated in the continental air masses samples. As a result, the aerosol chemical composition variability at the puy de D?me is a function of both the season and air mass type and we provide a chemical composition of the aerosol as a function of each of these environmental factors.  相似文献   

17.
北京不同区域气溶胶辐射效应   总被引：1，自引：0，他引：1       下载免费PDF全文
采用大气辐射传输模式SES2以及2013年1月—2015年10月欧洲中期天气预报中心细网格再分析资料计算了北京地区4个观测站地面接收的短波辐射通量,分析了晴天和云天北京城郊气溶胶对总辐射的定量影响时空变化特征。结果表明:北京城区和近郊区气溶胶对总辐射的影响约为远郊区的2倍,北京南部和西部气溶胶对辐射的影响较大,晴天和云天北京城区和近郊区气溶胶对总辐射的削减值分别为146.23~180.99 W·m-2和202.11~217.02 W·m-2,晴天总辐射削减空间差异较大;秋冬季气溶胶对总辐射的影响明显大于春夏季,北京市观象台秋冬季气溶胶对总辐射的削减作用最大可达60%,较春夏季高10%~20%;北京城郊总辐射和直接辐射削减率与气溶胶光学厚度变化均呈线性关系,近地面PM2.5浓度对辐射的影响不容忽视。  相似文献   

18.
Soil dust aerosol is the largest contributor to aerosol mass concentrations in the troposphere and has considerable effects on air quality and climate. Arid and semi-arid areas of East Asia are one of the important dust source regions thus it is crucial to understand dust mobilization and accurately estimate dust emissions in East Asia. However, present dust models still contain large uncertainties with dust emissions that remain a significant contributor to the overall uncertainties in the model. In this study, we attempt to reduce these uncertainties by using an inverse modeling technique and obtain optimized dust emissions. We use Moderate Resolution Imaging Spectrometer (MODIS) aerosol optical depths (AODs) and groundbased mass concentrations of particles less than 10 μm in aerodynamic diameter (PM10) observations over East Asia in May 2007. The MODIS AODs are validated with AErosol RObotic NETwork (AERONET) AODs. The inversion uses the maximum a posteriori method and the GEOS-Chem chemical transport model (CTM) as a forward model. The model error is large over dust source regions including the Gobi Desert and Mongolia. We find that inverse modeling analyses from the MODIS and PM10 observations consistently result in decrease of dust emissions over Mongolia and the Gobi Desert. Whereas over the Taklamakan Desert and Manchuria, the inverse modeling analyses from both observations yield contrast results such as increase of dust sources using MODIS AODs, while decrease of those using PM10 observations. We discuss some limitations of both observations to obtain the optimized dust emissions and suggest several strategies for the improvement of dust emission estimates in the model.  相似文献   

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