中国海洋上空细粒子气溶胶与短寿命痕量气体的时空关系

定量分析气溶胶与痕量气体之间的时空变化关系有助于进一步研究气粒转化。本文采用2006年—2015年MODIS气溶胶光学厚度(AOD)、细粒子模态比(FMF)和OMI痕量气体(SO_2、NO_2和HCHO)数据,对黄海、东海和南海区域上空的细粒子气溶胶与痕量气体进行定量分析。先对气溶胶和痕量气体作均值分析发现:AOD_(fine)、SO_2、NO_2和HCHO的均值在黄海、南海、东海均依次减小;再对气溶胶对痕量气体的敏感度分析发现:黄海地区的AOD_(fine)对SO_2最敏感,敏感度为0.424,这与中国东部沿海城市的人为排放有关;而东海和南海地区对HCHO的敏感度较高,依次为0.664和0.545,主要受东南亚和中国南方地区生物质燃烧影响。最后,对3个区域的气溶胶与痕量气体按季节作相关性分析发现:黄海地区AOD_(fine)在夏秋两季与SO_2的相关性较强(R0.5),主要由于夏秋两季的温湿度大,利于发生气—粒转化;东海地区夏季HCHO与AOD_(fine)相关性较明显(R=0.57);南海春季HCHO与AOD_(fine)相关性较好(R=0.57),呈现出区域与季节性的变化。最终发现,气溶胶与痕量气体随着时空变化存在相关关系。     

中国北方地区春季气溶胶光学特性地基遥感研究

基于中国北方地区地基太阳直接/散射辐射计观测,分析了2001年春季气溶胶光学厚度、尺度和吸收特性。沙尘期间,气溶胶光学厚度显著升高,而尺度上升,粗粒子浓度显著增加,大气气溶胶表现出中性或异常消光特征。除沙尘活动之外,中国华北地区人为排放也是导致气溶胶光学厚度偏高的一个重要原因。中国沙尘源区气溶胶单次散射反照率小于以往观测和模式结果。北京和香河两地气溶胶光学厚度、Angstrom指数和尺度谱基本相似,说明华北地区人为排放与沙尘活动类似,也表现出区域尺度的特点。由于沙尘气溶胶与人为排放气溶胶相比,折射指数实部偏大、虚部偏小,从而北京地区沙尘期间单次散射反照率明显大于非沙尘期间,特别是在近红外波段,说明沙尘活动不仅可以通过增加气溶胶光学厚度,同时也通过改变气溶胶物理、辐射特性来影响下游地区的气溶胶辐射强迫。     

Urban aerosol mapping over Athens using the differential textural analysis (DTA) algorithm on MERIS-ENVISAT data

Low and moderate spatial resolution satellite sensors (such as TOMS, AVHRR, SeaWiFS) have already shown their capability in tracking aerosols at a global scale. Sensors with moderate to high spatial resolution (such as MODIS and MERIS) seem also to be appropriate for aerosol retrieval at a regional scale. We investigated in this study the potential of MERIS-ENVISAT data to resolve the horizontal spatial distribution of aerosols over urban areas, such as the Athens metropolitan area, by using the differential textural analysis (DTA) code. The code was applied to a set of geo-corrected images to retrieve and map aerosol optical thickness (AOT) values relative to a reference image assumed to be clean of pollution with a homogeneous atmosphere. The comparison of satellite retrieved AOT against PM₁₀ data measured at ground level showed a high positive correlation particularly for the AOT values calculated using the 5th MERIS’ spectral band (R²=0.83). These first results suggest that the application of the DTA code on cloud free areas of MERIS images can be used to provide AOT related to air quality in this urban region. The accuracy of retrieved AOT mainly depends on the overall quality, the pollution cleanness and the atmospheric homogeneity of the reference image.     

中国地区气溶胶类型特性分析

利用全球气溶胶观测网（AERONET）2001年—2012年中国地区12个站点的地基遥感气溶胶物理光学特性产品研究了中国地区气溶胶类型特性及其时空变化规律。研究发现中国地区不同类别的气溶胶光学特性（单次散射反照率、不对称因子、光学厚度等）差异较大,由沙尘型、混合型、强散射型细粒子、弱吸收型细粒子、中度吸收型细粒子和强吸收型细粒子等6类组成。中国地区气溶胶类型具有极强的空间变化特性和明显的季节、年际变化特征,沙尘气溶胶主要出现在春季,强散射型细粒子气溶胶主要出现在夏季,而强吸收型细粒子气溶胶主要出现在秋冬季节;近10年间沙尘型、混合型和强散射型细粒子气溶胶呈现上升趋势,而强吸收型细粒子气溶胶则处于下降趋势。在此基础上对比了中国和美国、法国典型站点气溶胶类型,研究发现3个站点的气溶胶差异较大,中国强吸收细粒子类所占的比重高于后两者,同时强散射细粒子类所占的比重低于后两者。     

POLDER-2PARASOL卫星气溶胶业务产品在北京地区的验证分析

利用地面AERONET/PHOTONS气溶胶观测网北京和香河站点的资料,在北京地区对POLDER12/PARAsOL卫星多角度偏振信息获得的气溶胶反演产品进行了验证分析.地基AERONET/PHOTONS观测网的体积谱分布资料分析显示,在北京地区气溶胶尺度分布的细粒子截断半径约为0.3um.将POLDER-2/PARASOL卫星气溶胶业务产品和重新定义的地基AERONET/PHOTONs细模态(半径r<0.3p.m)气溶胶光学厚度(AOT)比较,两者在北京地区有着很好的一致性,说明卫星的气溶胶业务反演产品表征了主要来自人类污染排放的细粒子气溶胶贡献.然而,由于POLDER系列卫星业务反演方法固定了埃斯屈朗(Angstrom)指数的变化范围是1.8-3.0造成了细粒子贡献占绝对主导的局限.由地基AERONET/PHOTONS观测资料的分析可知,这个埃斯屈朗指数的先验值远远大于北京地区的地基测量结果,导致了POLDER业务反演的气溶胶光学厚度偏低,埃斯屈朗指数偏高.     

Atmospheric pollution assessment near potential source of natural aerosols in the South Gobi Desert region,China

ABSTRACT

Rapid economic growth, a high degree of urbanization and the proximity of a large number of desert and semidesert landscapes can have a significant impact on the atmosphere of adjacent territories, leading to high levels of atmospheric pollution. Therefore, identifying possible sources of atmospheric pollution is one of the main tasks. In this study, we carried out an analysis of spatial and temporal characteristics of five main atmospheric pollutants (PM_2.5, PM₁₀, SO₂, NO₂, and CO) near potential source of natural aerosols, affecting seven cities (Wuhai, Alashan, Wuzhong, Zhongwei, Wuwei, Jinchang, Zhangye), located in immediate proximity to the South Gobi deserts. The results, obtained for the period from 1 January 2016 to 31 December 2018, demonstrate total concentrations of PM_2.5 and PM₁₀ are 38.2 ± 19.5 and 101 ± 80.7 μg/m³ exceeding the same established by the Chinese National Ambient Air Quality Standard (CNAAQS), being 35 and 70 μg/m³, respectively. Based on the data from Moderate Resolution Imaging Spectroradiometer (MODIS) for the whole period, Clean Сontinental (71.49%) and Mixed (22.29%) types of aerosols prevail in the region. In the spring and winter seasons maximum concentrations of pollutants and high values of Aerosol Optical Depth (AOD) in the region atmosphere are observed. PM_2.5 and PM₁₀ ratio shows the presence of coarse aerosols in the total content with value 0.43. The highest concentrations of pollutants were in the period of dust storms activity, when PM_2.5 and PM₁₀ content exceeded 200 and 1000 µg/m³, and AOD value exceeded 1. UV Aerosol Index (UVAI), Aerosol Absorbing Optical Depth (AAOD), and Single Scattering Albedo (SSA), obtained from Ozone Monitoring Instrument (OMI), demonstrate the high content of dust aerosols in the period of sandstorms. Analysis of backward trajectories shows that dust air masses moved from North to Northwest China, affecting large deserts such as Taklamakan, Gurbantunggut, Badain Jaran, Tengger, and Ulan Buh deserts.     

Asian Dust Storm Monitoring Combining Terra and Aqua MODIS SRB Measurements

Sand and dust storms (SDSs), which present environmental risks and affect the regional climate, have been worsened in the East Asian regions over the last decade. Monitoring SDS from space using satellite remote sensing (RS) has become one of the most important issues in this field. At present, satellite RS of SDS is limited to using true-color images or aerosol optical thickness (AOT), or a new algorithm called "Deep Blue". Using current existing approaches makes it difficult to identify SDS from clouds. The authors have detected SDS by combining Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) solar reflectance band (SRB) measurements. Based on the dust spectral characteristic, this letter proposes a normalized difference dust index (NDDI) using MODIS reflectance measurements and applies it to the Asian SDS cases. The simple NDDI index is found to be able to identify SDS and clouds easily. The results suggest that NDDI could be used to detect SDS over bright surfaces where the MODIS AOT product is not available     

Seasonal and inter-annual variability of atmosphere CO<Subscript>2</Subscript> based on NOAA Carbon Tracker analysis and satellite observations

A study on seasonal and inter-annual variability of the atmospheric CO₂ is carried out based on National Oceanic and Atmospheric Administration Carbon Tracker (NOAACT) re-analysis and satellite measurements of mid-troposphere CO₂ by Atmosphere Infrared Sounder on board NASA’s Aqua and lower troposphere CO₂ by Greenhouse-gas Observing Satellite. Seasonal and non-seasonal components of each time series were extracted by means of least square based harmonic analysis procedure. The data of surface CO₂ fluxes used in the NOAACT are also analyzed to examine its relationship with the atmosphere CO₂ variability at different time scales. There exists good consistency between NOAACT analysis and satellite observations in their respective seasonal harmonics and climatology. Surface layer CO₂ exhibits large climatological mean over the regions of major anthropogenic sources together with strong seasonal cycle over the humid and cold climatic terrestrial regions especially over the northern hemisphere. Existence of high coherency with the different components of the surface fluxes shows that surface layer atmosphere CO₂ seasonality is primarily contributed from the terrestrial ecosystem exchanges and secondarily by anthropogenic and oceanic exchanges. The mid-troposphere CO₂ exhibits large values associated with climatology and amplitudes of semi-annual and annual cycles over the northern extra tropics and Polar Regions along with a gradual decreasing trend from northern to southern hemisphere. Inter-annual variability of atmospheric CO₂ in the NOAACT in some extent is consistent with the satellite observations. Large scale circulation patterns, its fluctuations associated with ENSO events and large scale ecosystem disturbances have significant influence on the inter-annual variability.     

Forest Fire Burnt Area Assessment in the Biodiversity Rich Regions Using Geospatial Technology: Uttarakhand Forest Fire Event 2016

The hills of Uttarakhand witness forest fire every year during the summer season and the number of these fire events is reported to have increased due to increased anthropogenic disturbances as well as changes in climate. These fires cause significant damage to the natural resources which can be mapped and monitored using satellite images by virtue of its synoptic coverage of the landscape and near real time monitoring. This study presents burnt area assessment caused by the fire episode of April 2016 to the forest vegetation. Digital classification of satellite images was done to extract the burnt area which was found to be 3774.14 km², representing 15.28% of the total forest area of the state. It also gives an account of cumulative progression of forest fire in Uttarakhand using satellite images of three dates viz. 23rd, 27th May and 2nd June, 2016. Results were analyzed at district, administrative and forest division level using overlay analysis. Separate area statistics were given for different categories of biological richness, forest types and protected areas affected by forest fire. The burnt area assessment can be used in mitigation planning to prevent drastic ecological impacts of the forest fire on the landscape.     

Large dust absorption of infrared radiation over Afro-Asian regions: evidence for anthropogenic impact

There is a large uncertainty in the estimation of dust radiative forcing due to the lack of adequate data about complex spatial and temporal pattern of the radiative properties of dust. Here, we examine the temporal and spatial variability of dust absorption in the thermal infrared over the Afro-Asian regions using satellite data. Large dust absorption (nearly double compared to that of pure dust) was observed in regions with large anthropogenic influence, possibly due to deposition of black carbon on dust particles. While most of the recent estimates of global mean dust radiative forcing predicted net cooling, our studies indicate that there could be large heating due to dust over vast Afro-Asian regions. It appears that large dust heating is due to its interaction with anthropogenic black carbon.     

Analyzing CO2 concentration changes and their influencing factors in Indonesia by OCO-2 and other multi-sensor remote-sensing data

We used OCO-2 products and considered three factors that potentially affect CO₂ concentration in Indonesia: sea surface temperature (SST), forest fires and vegetation. From 2014 to 2016, CO₂ concentration in Indonesia showed a trend of increase, which is consistent with the global increase reported by the Greenhouse Gases Observing Satellite (GOSAT) Project. As an archipelago country, the results indicate that SST has a direct effect on the CO₂ concentration in Indonesia. Their changing exhibits similar fluctuations; meanwhile, CO₂ concentration and SST also presented positive correlation. In 2015, the number of fire hotspots suddenly increased to 140,699, because of occurrence of the worst forest fire. Due to special geographic conditions, forest fires did not induce CO₂ concentration changes in Indonesia, but CO₂ concentration in the corresponding islands showed a trend of increase. CO₂ concentration increased in Kalimantan during the occurrence of forest fire in September–October 2014, and CO₂ concentration increased in Kalimantan and Sumatra during the occurrence of forest fire in September–October 2015. Vegetation indices were stable and presented no correlation with CO₂ concentration. This study demonstrated that OCO-2 is capable of monitoring CO₂ concentration at a regional scale; additionally, an effective method for using OCO-2 Level 2 products is proposed.     

Development of an image based integrated method for determining and mapping aerosol optical thickness (AOT) over urban areas using the darkest pixel atmospheric correction method,RT equation and GIS: A case study of the Limassol area in Cyprus

This paper presents the development of an image-based integrated method for determining and mapping aerosol optical thickness (AOT). Using the radiative transfer (RT) equation, a methodology was developed to create a Geographical Information System (GIS) model that can visually display the AOT distribution over urban areas. In this paper, the model was applied to eleven Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) satellite images of Limassol, Cyprus during 2010 and 2011 to determine the AOT levels in Limassol Cyprus during satellite overpass. The study is innovative and unique in that the RT equation, satellite images, the darkest pixel (DP) method of atmospheric correction and GIS were integrated to derive AOT from satellite images and display the AOT distribution over an urban area without the input of any meteorological or atmospheric parameters. The accuracy of the algorithm was verified through statistical analysis by the strong agreement between the AOT values derived using the algorithm and the in situ AOT values from the ground-based sensors.     

The pyrogeography of sub-Saharan Africa: a study of the spatial non-stationarity of fire–environment relationships using GWR

This study analyses the relationship between fire incidence and some environmental factors, exploring the spatial non-stationarity of the phenomenon in sub-Saharan Africa. Geographically weighted regression (GWR) was used to study the above relationship. Environment covariates comprise land cover, anthropogenic and climatic variables. GWR was compared to ordinary least squares, and the hypothesis that GWR represents no improvement over the global model was tested. Local regression coefficients were mapped, interpreted and related with fire incidence. GWR revealed local patterns in parameter estimates and also reduced the spatial autocorrelation of model residuals. All the covariates were non-stationary and in terms of goodness of fit, the model replicates the data very well (R ² = 87%). Vegetation has the most significant relationship with fire incidence, with climate variables being more important than anthropogenic variables in explaining variability of the response. Some coefficient estimates exhibit locally different signs, which would have gone undetected by a global approach. This study provides an improved understanding of spatial fire–environment relationships and shows that GWR is a valuable complement to global spatial analysis methods. When studying fire regimes, effects of spatial non-stationarity need to be incorporated in vegetation-fire modules to have better estimates of burned areas and to improve continental estimates of biomass burning and atmospheric emissions derived from vegetation fires.     

广东省和江苏省大气甲醛时空变化对比分析

利用Aura/OMI月均甲醛对流层垂直柱浓度数据对2005年—2016年中国广东省和江苏省的大气甲醛的时空变化规律、不同排放源的前体物的潜在贡献进行了分析。甲醛在广东省主要集中在珠三角地区,在江苏省分布则相对较为均匀。2005年—2010年,随着经济发展,在两省都发现了大面积的甲醛增加趋势;相应的,在2011年—2016年,由于减排等治理措施的实施,在两省都有大面积的甲醛减少现象。广东省的甲醛主要呈现出春季、秋季高于冬季再高于夏季的特征;而江苏地区夏季甲醛浓度远高于其他季节,并与光照强度的季节性特征较为一致。此外,由于广东省甲醛分布的均一性较差,因此区域性因素(如地形等)对广东省甲醛分布可能有着较大的影响。各个排放源中,工业源、交通源对珠三角潜在贡献可能较大;自然源对梅州等林地覆盖地区可能有相对较高的影响;在江苏省,各个排放源对甲醛的贡献相对均衡,但夏季较为频繁的生物质燃烧可能对夏季高值甲醛有着相对较高的贡献。     

Study on Regional Variations of Aerosol Loading Using Long Term Satellite Data Over Indian Region

Satellite-based measurements of aerosols are one of the most effective ways to understand the role of aerosols in climate in terms of spatial and temporal variability. In the present study, we attempted to analyse spatial and temporal variations of satellite derived aerosol optical depth (AOD) over Indian region using moderate resolution imaging spectrometer over a period of 2001–2011. Due to its vast spatial extent, Indian region and adjacent oceanic regions are divided into different zones for analysis. The land mass is sub divided into five different zones such as Indo Gangetic Plain (IGP), Indian mainland, North Eastern India (NE), South India-1 (SI-1), South India-2 (SI-2). Oceanic areas are divided into Arabian Sea and Bay of Bengal. Arabian Sea is further divided as three zones viz. Northern AS (NAS), Central AS (CAS) and Eastern AS (EAS) zones. Bay of Bengal is divided as North BoB (NBoB), West BoB (WBoB), Central BoB (CBoB), and East BoB (EBoB). The study revealed that among all the land regions, IGP showed the highest peak AOD value (0.52 ± 0.17) while SI-2 showed the lower values of AOD in all the months compared to all India average. The maximum AOD is observed during premonsoon season for all regions. During the winter, average AOD levels were substantially lower than the summer averages. Peak of aerosol loading (0.35 ± 0.159) is observed in March over NE region, whereas in all other regions, peak is observed during May. Frequency distribution of long term AOD (<0.2, 0.3–0.5, >0.5) shows a shift of frequency distribution of AOD from <0.3 to 0.3–0.5 during the study period in all regions except IGP. In IGP shift of frequency of AOD values occurs from 0.3–0.5 to >0.5. Oceanic areas also shows seasonal variation of AOD. Over Arabian Sea, high AOD values with greater variations were observed in summer monsoon season while in Bay of Bengal it is observed during winter monsoon. This is due to the high wind speed prevailing in Arabian Sea during monsoon season which results in production of more sea salt aerosol. Highest AOD values are observed over NAS during monsoon season and over NBOB during winter season. Lowest AOD values with its lower variations observed in both the central region of Arabian Sea and Bay of Bengal.     

GOSAT卫星数据监测中国大陆上空CO2浓度时空变化特征

中国地区大气CO2浓度对全球气候变化有重要的影响。本文基于日本GOSAT卫星短波红外CO2的长期观测数据,对2010年-2016年中国大陆上空CO2浓度的分布特征和变化趋势进行分析研究。利用高精度的地基TCCON站点CO2观测对GOSAT CO2数据进行精度验证,结果表明,GOSAT CO2具有较高的精度,相对TCCON CO2的偏差为-1.04±2.10 ppm,两者的相关系数高达0.90;利用中国地区7年的GOSAT CO2观测数据分析研究显示,CO2浓度高值主要分布在中国的浙江-江苏-安徽地区、京津冀地区和湖南-湖北-河南-陕西地区;截至2016年,中国大部地区CO2浓度超过400 ppm;中国大陆CO2平均浓度呈现明显的逐年增长趋势,从2010年的387.76 ppm增长到2016年的402.18 ppm,年增长率约为2.31 ppm/a,略高于同期全球平均水平。     

Analyzing ice dynamics using Sentinel-1 data at the Solheimajoküll Glacier,Iceland

ABSTRACT

The climate in southern Iceland has warmed over the last 70 years, resulting in accelerated glacier dynamics at the Solheimajoküll glacier. In this study, we compare glacier terminus locations from 1973 to 2018, to changes in climate across the study area, and we derive ice-surface velocities (2015–2018) from satellite remote-sensing imagery (Sentinel-1) using the offset-tracking method. There have been two regional temperature trends in the study period: cooling (1973–1979) and warming (1980–2018). Our results indicate a time lag of about 20 years between the onset of glacier retreat (?53 m/year since 2000) and the inception of the warming period. Seasonally, the velocity time series suggest acceleration during the summer melt season since 2016, whereas glacier velocities during accumulation months were constant. The highest velocities were observed at high elevations where the ice-surface slope is the steepest. We tested several scenarios to assess the hydrological time response to glacier accelerations, with the highest correlations being found between one and 30 days after the velocity estimates. Monthly correlation analyses indicated inter-annual and intra-annual variability in the glacier dynamics. Additionally, we investigate the linkage between glacier velocities and meltwater outflow parameters as they provide useful information about internal processes in the glacier. Velocity estimates positively correlate with water level and negatively correlate with water conductivity between April and August. There is also a disruption in the correlation trend between water conductivity and ice velocity in June, potentially due to a seasonal release of geothermal water.     

多样地表和大气状况下的MODIS数据云检测

云覆盖作为天气和气候变化的一个重要因子,对地表-大气能量平衡和水循环有着重要的影响,因此,快速、准确地利用卫星遥感技术检测云覆盖具有重要的实用价值和科学意义。利用卫星遥感数据,尤其是常用的Moderate Resolution Imaging Spectroradiometer(MODIS)影像数据,因其具有较高的光谱和时间分辨率,以及2330 km扫描幅宽,为大范围实时、准确地进行云检测提供了可能。目前,基于MODIS数据发展了大量的云检测方法,但因地表类型的多样性和大气状况(如空气污染和沙尘事件等)的复杂性,目前已有的云检测方法,检测精度通常具有较大的不确定性,且针对不同地表和大气状况缺乏普适性,同时也缺乏对检测精度的定量化评估。因此,本文首先比较了常用的3种云检测算法,并基于前人经验提出了两种改进方法(方法4和方法5),首先区分出云和冰雹,摒弃了不稳定的亮温波段,两种算法均适用于复杂地表和大气状况的云检测算法。结果显示,方法5可以较好地应用于基于MODIS数据的云检测,总体精度达92.6±7%,改进了现有基于MODIS数据的云检测算法;方法4平均总体精度82.9±13%,虽然精度相对较低,但云残留少,适合作为对云敏感度高的研究工作的云检测方法。     

Monitoring of Snow Cover Variability in Chenab Basin Using IRS AWiFS Sensor

Monitoring of seasonal snow cover is important for many applications such as melt runoff estimation, climate change studies and strategic requirements. Contribution of seasonal snow melt runoff of Chenab River is significant and important to meet hydrological requirement at foothills. Seasonal snow cover of Chandra, Bhaga, Miyar, Bhut, Warwan and Ravi, six major tributaries of Chenab River, becomes crucial to assess the water availability. In addition, altitudinal distribution of snow cover significantly influences the melt runoff which is highly sensitive to minor variations in atmospheric temperature. In this investigation, remote sensing based Normalized Difference Snow Index technique has been used to generate 10 daily snow cover product. Snow cover monitoring of all the sub-basins were carried out for 10 years from 2004–2005 to 2013–2014 during hydrological year (October to June) using Advanced Wide Field Sensor (AWiFS) of Indian remote sensing satellite (IRS). Accumulation and ablation patterns of snow cover have also been analyzed for the six sub-basins. Accumulation and ablation pattern of snow cover, from 2004 to 2014 which shows slightly increasing trend for all the sub-basins. Meteorological data of Kelong at Bhaga sub-basin was also analysed. Average monthly snow line altitude was estimated for all the sub-basins using hypsographic curve. Chandra and Bhaga sub-basins are at higher altitude and Ravi sub-basin is at lower altitude. It was also observed that areal extent of snow reaches to lower altitude during last 5 years, particularly in Ravi sub-basin.     

MODIS和OMI数据评估阅兵期间北京市大气减排成效

卫星观测不仅能反映区域宏观大气污染状况,也能从城市尺度上监测大气污染物的变化。基于以上优势,本文利用MODIS气溶胶光学厚度(AOD)和OMI对流层NO_2垂直柱浓度数据,比较2015年与2012年—2014年以及2015年3个时期(减排前、减排中、减排后)AOD和NO_2柱浓度的变化,定性分析了阅兵期间华北平原地区污染物减排效果,重点定量评估北京市联控减排措施的效果。研究发现2015年减排中华北平原重污染地区AOD和NO_2柱浓度相比于前3年同期有明显降低。定量分析北京市的减排效果得到:2015年减排中较前3年同期而言,AOD降低59%,NO_2柱浓度降低41%;较2015年减排前而言,AOD降低73%,NO_2柱浓度降低30%,去除气象条件影响后,AOD下降43%,NO_2柱浓度下降21%,说明严格的联控减排措施有效地改善了空气质量,气象条件也起到积极的作用。减排措施结束后,AOD和NO_2柱浓度比减排中分别增加159%和71%。研究结果表明,卫星遥感与地基监测评估效果相当,能反映北京地面污染物排放能力;它既能观测区域尺度大气污染变化,又可评估城市尺度大气污染减排。随着卫星技术水平的提高,期望未来卫星遥感可作为一种独立手段来定量评估区域及城市尺度空气质量减排措施的效果。