Himawari-8气溶胶产品的验证及应用

为准确分析中国地区气溶胶空间分布与时间变化特征规律,首先利用中国地区9个AERONET（Aerosol Robotic Network）地基站点观测资料对新一代静止气象卫星Himawari-8气溶胶光学厚度（Aerosol Optical Depth, AOD）产品数据进行一致性验证,并在此基础上选取2015年7月至2018年4月Himawari-8逐小时AOD数据分析了中国地区气溶胶光学厚度时空变化特征。结果表明：①Himawari-8 AOD与AERONET AOD之间相关性很高,9个站点的相关系数R在0.64 ~ 0.91之间,拟合曲线斜率k的范围为0.57 ~ 0.68。②Himawari AOD产品与AERONET AOD的相关性在中午时段较其他时段相对较低;北方地区Himawari-8 AOD冬季反演效果与夏季相比较差,南方地区则相反。③中国地区年平均AOD呈东高西低分布,春、夏两季AOD明显高于秋、冬两季,其中夏季最高,春季次之;地区间AOD月变化差异也较大;大部分地区AOD日变化呈现先下降后上升再下降的趋势,AOD最高值出现在午后14 ~ 16时,最低值出现在18时。研究结果为了解中国地区大气气溶胶的时空变化规律和全天时的大气污染监测方法提供新的参考。     

Himawari-8气溶胶产品的验证及应用

为准确分析中国地区气溶胶空间分布与时间变化特征规律，首先利用中国地区9个AERONET（Aerosol Robotic Network）地基站点观测资料对新一代静止气象卫星Himawari-8气溶胶光学厚度（Aerosol Optical Depth, AOD）产品数据进行一致性验证，并在此基础上选取2015年7月至2018年4月Himawari-8逐小时AOD数据分析了中国地区气溶胶光学厚度时空变化特征。结果表明：①Himawari-8 AOD与AERONET AOD之间相关性很高，9个站点的相关系数R在0.64 ~ 0.91之间，拟合曲线斜率k的范围为0.57 ~ 0.68。②Himawari AOD产品与AERONET AOD的相关性在中午时段较其他时段相对较低；北方地区Himawari-8 AOD冬季反演效果与夏季相比较差，南方地区则相反。③中国地区年平均AOD呈东高西低分布，春、夏两季AOD明显高于秋、冬两季，其中夏季最高，春季次之；地区间AOD月变化差异也较大；大部分地区AOD日变化呈现先下降后上升再下降的趋势，AOD最高值出现在午后14 ~ 16时，最低值出现在18时。研究结果为了解中国地区大气气溶胶的时空变化规律和全天时的大气污染监测方法提供新的参考。     

Himawari-8气溶胶产品的验证及应用

为准确分析中国地区气溶胶空间分布与时间变化特征规律,首先利用中国地区9个AERONET(Aerosol Robotic Network)地基站点观测资料对新一代静止气象卫星Himawari-8气溶胶光学厚度(Aerosol Optical Depth,AOD)产品数据进行一致性验证,并在此基础上选取2015年7月至2018年4月Himawari-8逐小时AOD数据分析了中国地区气溶胶光学厚度时空变化特征。结果表明:①Himawari-8 AOD与AERONET AOD之间相关性很高,9个站点的相关系数R在0.64～0.91之间,拟合曲线斜率k的范围为0.57～0.68。②Himawari AOD产品与AERONET AOD的相关性在中午时段较其他时段相对较低;北方地区Himawari-8 AOD冬季反演效果与夏季相比较差,南方地区则相反。③中国地区年平均AOD呈东高西低分布,春、夏两季AOD明显高于秋、冬两季,其中夏季最高,春季次之;地区间AOD月变化差异也较大;大部分地区AOD日变化呈现先下降后上升再下降的趋势,AOD最高值出现在午后14～16时,最低值出现在18时。研究结果为了解中国地区大气气溶胶的时空变化规律和全天时的大气污染监测方法提供新的参考。     

乌海矿区AOD时空变化特征及影响因素

针对大气低空间分辨卫星遥感数据不能准确反映长时间序列矿区小尺度区域的大气环境问题,利用MODIS MAIAC高分辨率数据,分析2003—2018年乌海矿区气溶胶光学厚度(aerosol optical depth,AOD)时空变化特征,采用Theil-Sen median趋势分析、Mann-Kendall检验方法、Pearson相关系数法,分析像元尺度AOD空间变化趋势和AOD与6个影响因子的相关性。结果表明,乌海矿区年际和季度AOD空间分布有明显的差异;乌海矿区年际AOD均值整体呈下降趋势,季度AOD变化秋季最高,春季和冬季较高,夏季最低;大尺度AOD与人为因子呈正相关关系,与自然因子无显著相关性;像元尺度AOD与人为因子和气温因子呈正相关性分布,在中部煤矿开采区及工业园区,与风速和降水因子呈强负相关性分布,在南部,与植被指数的相关性呈分散分布。     

中国东南地区及近海海域气溶胶反演遥感研究

大气气溶胶在很多生物地球化学循环中具有重要作用,但是由于它的来源广泛并且具有很大的时空变化性,难以在全球范围内精确、实时确定气溶胶的性质、组成及时空分布,因而对大气气溶胶的研究依赖于监测手段的发展。地基试验能获取点源的大气气溶胶光学厚度(AOD)的地面测量数据,得到的气溶胶光学厚度用于卫星数据的预处理以及气溶胶光学厚度反演的精度验证。而经过地基校验后的卫星遥感数据,可以反映大范围内实时动态的气溶胶信息。利用MODIS资料和地基探测的太阳光度计资料,对中国东南地区及近海海域的大气气溶胶光学特性进行了分析,讨论了适用于中国东南地区的大气气溶胶模型;利用连续的太阳光度计数据对MODIS资料的反演结果进行校验,结果表明：改进气溶胶模型和采用连续波段太阳光度计探测数据,可以提高MODIS AOD的校验结果。     

广州市晴空气溶胶光学特性及源特征分析

利用CE318太阳光度计观测数据反演了广州市2015年晴空气溶胶的基本光学特性,分析其时间变化特征及探究本地污染来源,并基于HYSPLIT后向轨迹模型研究了广州大气污染外部输送来源的特征。结果表明:①2015年广州市AOD年均值为0.625,处于较高的水平。其中,春季AOD值最大,其余依次为秋季、冬季、夏季,具有明显的季节变化特征;②气溶胶基本光学特性的日变化与人类活动密切相关,道路交通污染是大气气溶胶的主要来源;③大气污染受外部输送的影响具有明显的季节变化特征,与本地排放叠加,使得广州大气污染加重,且常年有海洋性粒子输送;④各个季节波长指数均大于1,主要分布在0.8～1.4区间内,全年气溶胶组分稳定,以较小粒径的气溶胶为主。总体看来,广州地区气溶胶类型主要为城市—工业型和海洋性气溶胶的混合类型。     

利用MODIS遥感监测可吸入颗粒物PM10的研究

为了研究利用卫星遥感方法监测大范围可吸入颗粒物的空间分布,本文在利用MODIS卫星资料反演河北省晴天大气气溶胶光学厚度的基础上,将河北省11个城市地面监测站的可吸入颗粒物PM10浓度值与对应的大气气溶胶光学厚度AOD值作了相关分析,建立了大气气溶胶光学厚度AOD与PM10的关系模型,相关系数为O．5390,达到了O．001以上的显著水平。经多次应用效果检验,平均误差为17％。结果表明,利用晴天AOD与地面PM10质量浓度的关系模型可以有效地监测PM10的空间分布。     

利用MODIS遥感监测PM10的方法研究

本文为了研究利用卫星遥感方法监测大范围可吸入颗粒物的空间分布,在利用MODIS卫星资料反演河北省晴天大气气溶胶光学厚度的基础上,将河北省11个城市地面监测站的可吸入颗粒物PM10浓度值与对应的大气气溶胶光学厚度AOD值作了相关分析,建立了大气气溶胶光学厚度AOD与PM10的关系模型,相关系数为O．5590,达到了0．001以上的显著水平。经多次应用效果检验,平均误差为17％。结果表明,利用晴天AOD与地面PM10质量浓度的关系模型可以有效地监测PM10的空间分布。     

基于Himawari-8的气溶胶反演研究

为获取中国区域高时空分辨率、高精度的气溶胶光学厚度（AOD）产品。基于Himawari-8卫星数据和MODIS地表反射率产品,反演了中国区域2018年4月~2019年4月逐10分钟的AOD,该方法可同时对暗像元、亮像元区域进行反演。依托全球气溶胶观测网（AERONET）中国境内的6个观测站数据,对反演结果进行一致性检验,同时将AOD反演结果与Himawari-8官方最新发布的AOD产品（020版）进行对比。结果表明：①红蓝比值法AOD反演结果与AERONET AOD之间相关性很高,除包头站外,其余5个站点的相关系数R在0.728~0.863之间,EE（误差期望）范围内样本点百分比在47.7%~68.6%之间,与Himawari-8 AOD产品相比有很大优势;②红蓝比值法AOD反演结果与AERONET AOD在时间序列走势上基本一致,但在AOD >1时,反演结果较AERONET AOD偏高。Himawari-8 AOD春夏季走势相对于AERONET AOD较为一致,但由于秋冬季Himawari-8 AOD有明显的日变化,且日变化较大,其走势与AERONET AOD偏离较大;③红蓝比值法AOD反演结果与MODIS AOD产品空间分布基本一致,AOD反演结果总体较MODIS AOD略为偏低。在冬季时红蓝比值法反演范围较MOD04_3K AOD的反演范围广;④红蓝比值法AOD在冬春季的北方高反射率地表区域的反演结果精度和反演范围较Himawari-8 AOD产品和MOD04_3K产品有很大优势。     

气溶胶光学厚度、类型及廓线对CO2反演的敏感性分析

位于1.6和2.06 μm附近的短波红外波段可用于探测低层大气CO²信息,然而除大气分子(主要是CO²)吸收外,大气分子散射、气溶胶和云散射也是限制这些波段的卫星测量信号的主要因素,因此气溶胶光学参数及其垂直分布也必然制约着GOSAT(Greenhouse Gases Observing Satellite)CO²的反演精度。利用正演模式DISORT分析气溶胶光学厚度(AOD)、类型以及廓线对CO²反演精度的敏感性,旨在提高CO²反演精度。结果表明:①不同类型气溶胶AOD增大对CO²柱总量的影响各不相同,且CO²柱总量变化量的变化趋势也不相同,这取决于气溶胶的散射相函数与单次散射反照率的大小;②气溶胶类型变化会导致CO²柱总量变化,且这种变化随着AOD增大而增大;③对于满足指数分布的沙尘气溶胶,标高的低估会导致反演的CO²柱总量偏大,而气溶胶的集中分布导致反演的CO²柱总量偏小,且气溶胶层越高,反演的CO²柱总量越小。     

Analysis of Clear-Sky Aerosol Optical Properties and Source Characteristics in Guangzhou

The basic optical properties of clear-sky aerosol of Guangzhou in 2015 were retrieved using CE318 sun photometer data,and their temporal variation characteristics were analyzed and local pollution sources were explored.based on the HYSPLIT backward-trajectory model,the characteristics of external transport sources of air pollution in Guangzhou were studied.The results show that：（1) in 2015,the annual average AOD in Guangzhou is 0.625,which is at a relatively high level.Among them,AOD is the largest in spring,followed by autumn,winter,and summer,with obvious seasonal variations;（2) the daily variation of aerosol basic optical properties are closely related to human activities,and road traffic pollution is the main source of atmospheric aerosol;（3)Air pollution affected by external transport has obvious seasonal variation characteristics,which is superimposed with local emissions,causing air pollution in Guangzhou to be worse,and marine particles transport occurs all year round;（4) the wavelength exponent of all seasons is greater than 1,and is mainly distributed within the interval of 0.8 to 1.4.The aerosol components are stable throughout the year,mainly with smaller particle size aerosols.In general,the aerosol type in the Guangzhou area is mainly a mix of urban-industrial and marine aerosols.     

Spatial and temporal variations of aerosol optical depth in China during the period from 2003 to 2006

Spatial and temporal variations of aerosol optical depth (AOD, or τ) in China were investigated using MODIS-derived aerosol data for a period of 2003–2006. The geographical distribution patterns of 4-year mean AOD for total, τ_0.55 (AOD at 0.55 μm), fine, τ_0.55-fine, and coarse, τ_0.55-coarse, aerosols over China were addressed. These results indicate that the distribution of aerosol was largely affected by population, urban/industrial activity, agricultural biomass burning, spring dust, topography and humidity. τ_0.55-fine in eastern China is significantly higher than in western China. Distribution of τ_0.55-coarse reflected the influence of spring dust and urban/industrial pollution. The overall AOD in summer was higher than that in winter due to strong photochemical reactions producing secondary aerosols. In northern China, dust contributed to the mean τ_0.55 in spring months. In some places, aggregated precipitation in the summer months caused a pronounced drop in the temporal profile of AOD. Coal combustion, industrial emission and vehicle exhaust produced coarse aerosols, while fine aerosols are mainly dominated by secondary particles. Smoke from open-fire straw burning produced fine aerosols in the harvest season.     

Satellite remote sensing of fine particulate matter (PM2.5) air quality over Beijing using MODIS

Fine particulate matter (aerodynamic diameters of less than 2.5 µm, PM_2.5) air pollution has become one of the major environmental challenges, causing severe environmental issues in urban visibility, climate, and public health. In this study, ground-level PM_2.5 concentrations, air-quality categories (AQCs), and health risk categories (HRCs) over Beijing, China, have been estimated based on mid-visible column aerosol optical depth (AOD) measurements extracted from Moderate Resolution Imaging Spectroradiometer (MODIS) data on board both Terra and Aqua satellites. Our results indicate that the MODIS AOD retrievals at 550 nm (AOD₅₅₀) match hourly aerosol robotic network (AERONET) measurements with correlation coefficients (r) of 0.950 for Terra and 0.895 for Aqua. The relationship between ground-level PM_2.5 and MODIS AOD₅₅₀ from March 2012 to February 2013 showed correlation coefficients of 0.69, 0.60, and 0.73 for spring, summer, and autumn, respectively. The atmospheric boundary layer height and relative humidity (RH) adjustments improved the AOD–PM_2.5 relationship in summer months. The estimates of daily average PM_2.5 from satellite measurements were used to predict both AQCs and HRCs, which are well matched with observations. Satellite remote sensing of atmospheric aerosols continues to show great potential for estimating ground-level PM_2.5 concentrations and can be further used to monitor the atmospheric environment in China.     

Seasonal variation of columnar aerosol optical properties over Athens, Greece, based on MODIS data

A long-term (2000–2005) data set of aerosol optical properties obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) is analyzed focusing on the Greater Athens Area in the Eastern Mediterranean region. The MODIS aerosol optical depth standard product (AOD at 550 nm) and its respective ratio attributed to fine-mode particles (FM) are employed to evaluate the inter-annual and seasonal variability of the aerosol properties over Athens. Based on AOD₅₅₀ and FM values three specific aerosol types are discriminated corresponding to different aerosol load and optical properties. The aerosol types considered correspond to urban/industrial aerosols, coarse-mode particles and clean maritime conditions. This study focuses on the seasonal and year-to-year fluctuation of the number of occurrences as well as the AOD₅₅₀ and FM values of each aerosol type. The coarse-mode particles are observed mainly in the summer, while spring is the most favorable season for the occurrence of urban/industrial aerosols. On the other hand, clean maritime conditions occur mainly in the winter. The AOD₅₅₀ values for the coarse-mode particles are higher in spring, while the urban/industrial and clean maritime aerosols exhibit slightly higher values in the summer. The seasonal distribution of the aerosol properties is related to anthropogenic and dust emissions in the spring/summer period, but is modified by atmospheric dispersion and precipitation in late autumn/winter. The main conclusion of the study is that the coarse-mode particles exhibit much stronger inter-annual and seasonal variability compared to the urban/industrial aerosols. Finally, three cases corresponding to each aerosol type are analyzed with the aid of synoptic weather maps, air mass trajectories and MODIS data.     

Aerosol optical depth variability over the southeastern Arabian Sea

Aerosol optical depth (AOD), an index of aerosol concentration, is used to study atmospheric features. Accordingly, spatiotemporal variability of AOD in the atmospheric column over the southeastern Arabian Sea (SEAS) is investigated utilizing monthly data obtained from both the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), from September 1997 to December 2010, and the Moderate Resolution Imaging Spectroradiometer (MODIS) on board Aqua, from July 2002 to December 2010. A comparison between the data from both sensors showed similar averages (~0.13), but with different standard deviations (0.03 and 0.02) over the SEAS. The AOD distribution was found to be dominated by an annual cycle controlled by the monsoon climate, with maximum aerosol concentration during July/August (~0.2) and minimum during November/December (<0.1). Empirical mode decomposition (EMD) analysis revealed the influence of the Quasi-Biennial Oscillation (QBO) and El Niño Southern Oscillation (ENSO) in producing inter-annual variability of 2% and 1%, respectively. Simulated backwards trajectories of aerosols, using Hybrid Single-Particle Lagrangian Integrated Trajectory models, indicated two main remote sources, i.e. sea salt from the Arabian Sea and dust particles from the Arabian Peninsula are the key factors contributing to an increase in the concentration of aerosols over the study area during the southwest monsoon period, irrespective of the opposing phases of QBO.     

Aerosol optical depth spatio-temporal characterization over the Canadian BOREAS domain

A complete set of Advanced Very High Resolution Radiometer (AVHRR) data (75 images) is used to retrieve aerosol optical depth (AOD) over dense vegetation and over lake water in the visible AVHRR channel. The present approach for remote sensing of aerosols from the National Oceanic and Atmospheric Administration (NOAA)-11 AVHRR sensor is based on the detection of atmospherically dominated signals over dark surface covers such as dense dark vegetation (DDV). Such targets were identified using the reflective portion of the middle-wave AVHRR channel 3 signal. When a fixed DDV surface reflectance is subtracted from the observed reflectance after correction for all other atmospheric effects, the remaining part, which is due to aerosols, is inverted to derive aerosol optical thickness using a look-up table (LUT) similar to that used in water surface inversion. The algorithm was applied to the daily afternoon NOAA-11 AVHRR (1?km×1?km) data acquired from the end of May to mid-August 1994 over the Canadian 1000?km×1000?km Boreal Ecosystem Atmosphere Study (BOREAS) domain. A validation analysis using five ground-based Sun photometers within the studied area shows the good performance of the retrieval algorithm. The approach allows detailed analysis of the AOD spatio-temporal behaviour at the regional scale useful for climate and transport model validation.     

Distribution and transport of aerosols in the south Indian region and surroundings

The weather/climate of south India is entirely different from that of north India. So the aerosol loading and variability in the regions also show considerable difference. The present study investigates the aerosol distribution over the south Indian region. The transport of aerosols over the region is studied in detail and climate features of the region are investigated to understand the aerosol distribution of the region. In situ observations available in two stations in the west coast and equatorial Indian region and satellite data available for the region are used for the analysis. Aerosol concentration is less in south India compared to that in north India with AOD (aerosol optical depth) values above 0.5 in north India and below 0.4 in south India. The studies reveal the seasonal variability in aerosol loading with high aerosol concentration during summer (>0.4) and less loading during winter season (<0.3) in south India. In situ aerosol observations taken for the first time in Cochin station implies variability in coarse mode aerosols with AOD near 0.3 in summer and near 0.2 in winter. The seas surrounding south India have significant impact in the aerosol loading as they are the sources of marine aerosols such as sea-salt, sulphates etc. Exchange of aerosols takes place from the marine environment and land regions over south India and surroundings. The coastal region of south India experiences high aerosol loading during June to August period. Different climate pattern of the region and the presence of adjoining seas lead to a mixed aerosol content, which includes aerosols of marine and continental origin. In north India, anthropogenic and natural aerosols such as dust, black carbon etc. are dominant in the atmosphere.     

Dust storm and black cloud influence on aerosol optical properties over Cairo and the Greater Delta region,Egypt

We have analysed aerosol and cloud properties, obtained from moderate resolution imaging spectroradiometer (MODIS) data, over Cairo and the Greater Delta region during the spring months of March, April and May (MAM) and the autumn months of September, October and November (SON) in the years 2004, 2005 and 2006. During these two time periods, we have examined dust storms, dense haze and a smog‐like phenomenon known, locally, as the ‘black cloud’. Our work is based on the aerosol optical depth (AOD), fine mode fraction (FMF) and cloud properties (cloud top temperature (CTT), cloud top pressure (CTP), atmospheric infrared sounder (AIRS) temperature profiles and water vapour column). High anomalous water vapour is detected, which we believe is as a result of pollution aerosols rather than dust and is hence acting as cloud condensation nuclei (CCN). The CTT shows increasing and decreasing trends, corresponding to the dust occurring at ～750–800 hpa and pollution episodes at >900 hpa, respectively as observed from the CTP. Temperature inversion conditions, as well as adverse weather conditions, contribute to the pollution observed by preventing pollutants from escaping to the higher atmosphere.     

Validation of MODIS retrieval aerosol optical depth and an investigation of aerosol transport over Mohal in north western Indian Himalaya

This study deals with the optical properties of aerosols during 2007 over Mohal (31.9º N, 77.12º E) in north western Indian Himalaya, investigated using ground-based measurements and multi-satellite data. The daily average (mean ± standard deviation) aerosol optical depth (AOD) at 500 nm, Ångström exponent and turbidity coefficient values were 0.2 ± 0.1, 1.1 ± 0.3 and 0.1 ± 0.1, respectively. About 84% of AOD values retrieved from satellites were found to be within an uncertainty limit with a significant correlation coefficient around 0.70. The present study suggests that AOD retrieval using the Moderate Resolution Imaging Spectroradiometer (MODIS) is able to characterize AOD distribution over Mohal. However, to eliminate systematic errors, the existing MODIS algorithm needs to be modified in view of the changing aerosol optical properties, especially during the biomass-burning period. To investigate the influence of aerosol transport, a multi-sensor approach in conjunction with back-trajectory analysis was used. The observed higher values of AOD during dust-loading days with simultaneous study of the space-borne lidar measurements as well as back-trajectory analysis suggest the influx of desert aerosols. Transport of dust aerosols on 12 April, 27 April and 1 June caused a significant reduction in surface-reaching solar irradiance by 43, 40 and 39 W m^–2, respectively. Atmospheric forcing during these days increased by 33.8, 33.0 and 33.2 W m^–2, which translates into atmospheric heating rates of 0.95, 0.93 and 0.93 K day^–1, respectively. This indicates significant climatic implications due to arriving aerosols in north-western Indian Himalaya.