Ground-based and additional science support for SMILE

The joint European Space Agency and Chinese Academy of Sciences Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission will explore global dynamics of the magnetosphere under varying solar wind and interplanetary magnetic field conditions,and simultaneously monitor the auroral response of the Northern Hemisphere ionosphere.Combining these large-scale responses with medium and fine-scale measurements at a variety of cadences by additional ground-based and space-based instruments will enable a much greater scientific impact beyond the original goals of the SMILE mission.Here,we describe current community efforts to prepare for SMILE,and the benefits and context various experiments that have explicitly expressed support for SMILE can offer.A dedicated group of international scientists representing many different experiment types and geographical locations,the Ground-based and Additional Science Working Group,is facilitating these efforts.Preparations include constructing an online SMILE Data Fusion Facility,the discussion of particular or special modes for experiments such as coherent and incoherent scatter radar,and the consideration of particular observing strategies and spacecraft conjunctions.We anticipate growing interest and community engagement with the SMILE mission,and we welcome novel ideas and insights from the solar-terrestrial community.

Ground-Based Atmospheric CO_(2),CH_(4),and CO Column Measurements at Golmud in the Qinghai-Tibetan Plateau and Comparisons with TROPOMI/S5P Satellite Observations

Measurements of carbon dioxide(CO_(2)),methane(CH_(4)),and carbon monoxide(CO)are of great importance in the Qinghai-Tibetan region,as it is the highest and largest plateau in the world affecting global weather and climate systems.In this study,for the first time,we present CO_(2),CH_(4),and CO column measurements carried out by a Bruker EM27/SUN Fourier-transform infrared spectrometer(FTIR)at Golmud(36.42°E,94.91°N,2808 m)in August 2021.The mean and standard deviation of the column-average dry-air mixing ratio of CO_(2),CH_(4),and CO(XCO_(2),XCH_(4),and XCO)are 409.3±0.4 ppm,1905.5±19.4 ppb,and 103.1±7.7 ppb,respectively.The differences between the FTIR co-located TROPOMI/S5P satellite measurements at Golmud are 0.68±0.64%(13.1±12.2 ppb)for XCH_(4) and 9.81±3.48%(–10.7±3.8 ppb)for XCO,which are within their retrieval uncertainties.High correlations for both XCH_(4) and XCO are observed between the FTIR and S5P satellite measurements.Using the FLEXPART model and satellite measurements,we find that enhanced CH_(4) and CO columns in Golmud are affected by anthropogenic emissions transported from North India.This study provides an insight into the variations of the CO_(2),CH_(4),and CO columns in the Qinghai-Tibetan Plateau.

Modeling and Analysis of the Impacts of Temporal-Spatial Variant Troposphere on Ground-Based SAR Imaging of Asteroids

The near-Earth asteroid collisions could cause catastrophic disasters to humanity and the Earth,so it is crucial to monitor asteroids.Ground-based synthetic aperture radar(SAR)is an observation technique for high resolution imaging of asteroids.The ground-based SAR requires a long integration time to achieve a large synthetic aperture,and the echo signal will be seriously affected by temporal-spatial variant troposphere.Traditional spatiotemporal freezing tropospheric models are ineffective.To cope with this,this paper models and analyses the impacts of temporal-spatial variant troposphere on ground-based SAR imaging of asteroids.For the background tropo-sphere,a temporal-spatial variant ray tracing method is proposed to trace the 4D(3D spatial+temporal)refractive index network provided by the numerical weather model,and calculate the error of the background troposphere.For the tropospheric turbulence,the Andrew power spectral model is used in conjunction with multiphase screen theory,and varying errors are obtained by tracking the changing position of the pierce point on the phase screen.Through simulation,the impact of temporal-spatial variant tropospheric errors on image quality is analyzed,and the simulation results show that the X-band echo signal is seriously affected by the troposphere and the echo signal must be compensated.

采用MAX-DOAS观测北极新奥尔松地区夏季NO_2的柱浓度与垂直分布

多轴差分吸收光谱技术(MAX-DOAS)作为一种观测痕量气体成分的地基遥感手段,在反演过程中利用天顶谱扣除了平流层的影响,因而对底层大气的测定较为敏锐。采用地基被动MAX-DOAS在2011年7月5日—8月1日对北极新奥尔松地区的NO2柱浓度进行观测。观测期间4个离轴观测角的NO2差分斜柱浓度(DSCDs)结果显示,NO2主要集中在对流层底部。观测期间新奥尔松地区NO2的平均混合比为1.023E11molec.cm-3(0～1km),其含量的波动与轮船的化石燃料燃烧和大气光化学反应有关。3km内NO2的垂直分布图显示,NO2主要来自海洋边界层的释放,且随时间呈现波动变化。

华北地区香河站对流层NO_2的MAX-DOAS光谱仪观测及变化特征分析

利用中国科学院大气物理研究所香河大气探测综合试验站2010年3月至2012年2月（2年）的多轴差分吸收光谱仪（MAX—DOAS）观测数据和32m高塔常规气象资料，反演了华北地区香河站对流层NO2柱浓度，分析了该区域NO2柱浓度的季节变化特征。研究表明：可见光455×485nm、紫外330×370nm都可以作为MAX-DOAS工作波段很好地反演NO2；香河地区NO2柱浓度夏季最低，几乎保持在2×10^16cm^-2以下，春、秋季次之，在3×10^16cm^-2上下小范围浮动，冬季最高，可达4．5×10^16cm^-2；月平均最低值出现在7月，最高值出现在11月。NO2柱浓度与风速、风向密切相关：来自东边唐山方向的风，风速越大时NO2浓度越高，因为唐山是NO2的高值区之一；其它方向风速越大，浓度越低。春、夏两季NO2柱浓度日变化趋势比较平缓，秋、冬两季曰变化明显，秋季正午偏高，冬季早晚偏高。

基于MAX-DOAS的对流层NO_2和气溶胶光学厚度遥测反演

随着全球工业化速度加快和人口的增多,大气环境问题日益突出,NO_2和气溶胶在大气化学中扮演着重要的角色。地基多轴差分吸收光谱技术(MAX-DOAS)基于被动DOAS原理,近年来已成功应用于大气痕量气体柱浓度和气溶胶光学厚度(AOD)测量方面。基于被动DOAS算法对合肥秸秆燃烧期间NO_2柱浓度以及气溶胶光学厚度进行了观测,并把对流层柱浓度和臭氧监测仪(Ozone Monitoring Instrument,OMI)结果进行对比;测量的气溶胶光学厚度和太阳光度计(CE318)进行了对比。结果表明,MAX-DOAS测量结果要高于卫星值,11月6日MAX-DOAS测量NO_2柱浓度日均值为OMI的1.9倍;二者在无云条件下一致性较好;MAX-DOAS反演AOD和太阳光度计结果相关性在0.9以上。

淮北对流层NO_2柱浓度地基MAX-DOAS观测与OMI对比

利用地基MAX-DOAS仪器在2016年9—11月对淮北进行监测,获取NO2垂直柱浓度的时间序列并与OMI卫星进行对比.结果表明,在晴朗天气下两者具有较好的一致性(R2=0.804 6),在晴朗和阴天条件下卫星测量结果系统性低于MAX-DOAS结果,这主要是因为两种仪器观测方式和观测区域不同导致的.9—11月NO2月均值逐渐增加,其中11月的NO2相比9月的增加36.8%,说明淮北地区空气污染在观测时段内加重.研究结果表明,地基MAX-DOAS系统不仅可以对区域污染的演变进行研究,也能够为卫星结果提供验证.

Ground-Based Hyperspectral Stereoscopic Remote Sensing Network: A Promising Strategy to Learn Coordinated Control of O_(3) and PM_(2.5) over China

With the coming of the“14th Five-Year Plan,”the coordinated control of particulate matter with an aerodynamic diameter no greater than 2.5 lm(PM_(2.5))and O_(3) has become a major issue of air pollution prevention and control in China.The stereoscopic monitoring of regional PM_(2.5) and O_(3) and their precursors is crucial to achieve coordinated control.However,current monitoring networks are currently inadequate for monitoring the vertical profiles of both PM_(2.5) and O_(3) simultaneously and support air quality control.The University of Science and Technology of China(USTC)has established a nationwide ground-based hyperspectral stereoscopic remote sensing network based on multi-axis differential optical absorption spectroscopy(MAX-DOAS)since 2015.This monitoring network provides a significant opportunity for the regional coordinated control of PM_(2.5) and O_(3) in China.One-year vertical profiles of aerosol,NO_(2) and HCHO monitored from four MAX-DOAS stations installed in four megacities(Beijing,Shanghai,Shenzhen,and Chongqing)were used to characterize their vertical distribution differences in four key regions,Jing–Jin–Ji(JJJ),Yangtze River Delta(YRD),Pearl River Delta(PRD),and Sichuan Basin(SB),respectively.The normalized and yearly averaged aerosol vertical profiles below 400 m in JJJ and PRD exhibit a box shape and a Gaussian shape,respectively,and both show exponential shapes in YRD and SB.The NO_(2) vertical profiles in four regions all exhibit exponential shapes because of vehicle emissions.The shape of the HCHO vertical profile in JJJ and PRD was Gaussian,whereas an exponential shape was shown in YRD and SB.Moreover,a regional transport event occurred at an altitude of 600–1000 m was monitored in the southwest–northeast pathway of the North China Plain(NCP)by five MAX-DOAS stations(Shijiazhuang(SJZ),Wangdu(WD),Nancheng(NC),Chinese Academy of Meteorological Sciences(CAMS),and University of Chinese Academy of Sciences(UCAS))belonging to the above network.The aerosol optical depths(AOD)in these five stations decreased in the order of SJZ>WD>NC>CAMS>UCAS.The short-distance regional transport of NO2 in the 700–900 m layer was monitored between WD and NC.As an important precursor of secondary aerosol,the peak of NO_(2) air mass in WD and NC all occurred 1 h earlier than that of aerosol.This was also observed for the short-distance regional transport of HCHO in the 700–900 m layer between NC and CAMS,which potentially affected the O_(3) concentration in Beijing.Finally,CAMS was selected as a typical site to determine the O_(3)–NO_(x)–volatile organic compounds(VOCs)sensitivities in vertical space.We found the production of O_(3) changed from predominantly VOCs-limited conditions to mainly mixed VOCs–NO_(x)-limited condition from the 0–100 m layer to the 200–300 m layer.In addition,the downward transport of O_(3) could contribute to the increase of ground surface O_(3) concentration.This ground-based hyperspectral stereoscopic remote sensing network provide a promising strategy to support management of PM_(2.5) and O_(3) and their precursors and conduct attribution of sources.

Evaluation and Evolution of MAX-DOAS-observed Vertical NO_(2) Profiles in Urban Beijing

Multiaxis differential absorption spectroscopy(MAX-DOAS)is a newly developed advanced vertical profile detection method,but the vertical nitrogen dioxide(NO_(2))profiles measured by MAX-DOAS have not yet been fully verified.In this study,we perform MAX-DOAS and tower gradient observations to simultaneously acquire tropospheric NO_(2)observations in the Beijing urban area from 1 April to 31 May 2019.The average values of the tropospheric NO_(2)vertical column densities measured by MAX-DOAS and the tropospheric monitoring instrument are 15.8×1015 and 12.4×1015 molecules cm−2,respectively,and the correlation coefficient R reaches 0.87.The MAX-DOAS measurements are highly consistent with the tower-based in situ measurements,and the correlation coefficients R from the ground to the upper air are 0.89(60 m),0.87(160 m),and 0.76(280 m).MAX-DOAS accurately measures the trend of NO_(2)vertical profile changes,although a large underestimation occurs by a factor of two.By analyzing the NO_(2)vertical profile,the NO_(2)concentration reveals an exponential decrease with height.The NO_(2)vertical profile also coincides with the evolution of the boundary layer height.The study shows that the NO_(2)over Beijing mainly originates from local sources and occurs in the boundary layer,and its vertical evolution pattern has an important guiding significance to better understand nitrate production and ozone pollution.

0-10 KM TEMPERATURE AND HUMIDITY PROFILES RETRIEVAL FROM GROUND-BASED MICROWAVE RADIOMETER

Deviation exists between measured and simulated microwave radiometer sounding data. The bias results in low-accuracy atmospheric temperature and humidity profiles simulated by Back Propagation artificial neural network models. This paper evaluated a retrieving atmospheric temperature and humidity profiles method by adopting an input data adjustment-based Back Propagation artificial neural networks model. First, the sounding data acquired at a Nanjing meteorological site in June 2014 were inputted into the Mono RTM Radiative transfer model to simulate atmospheric downwelling radiance at the 22 spectral channels from 22.234 GHz to 58.8 GHz, and we performed a comparison and analysis of the real observed data; an adjustment model for the measured microwave radiometer sounding data was built. Second, we simulated the sounding data of the 22 channels using the sounding data acquired at the site from 2011 to 2013. Based on the simulated rightness temperature data and the sounding data, BP neural network-based models were trained for the retrieval of atmospheric temperature, water vapor density and relative humidity profiles. Finally, we applied the adjustment model to the microwave radiometer sounding data collected in July 2014, generating the corrected data. After that, we inputted the corrected data into the BP neural network regression model to predict the atmospheric temperature, vapor density and relative humidity profile at 58 high levels from 0 to 10 km. We evaluated our model's effect by comparing its output with the real measured data and the microwave radiometer's own second-level product. The experiments showed that the inversion model improves atmospheric temperature and humidity profile retrieval accuracy; the atmospheric temperature RMS error is between 1 K and 2.0 K; the water vapor density's RMS error is between 0.2 g/m^3 and 1.93 g/m3; and the relative humidity's RMS error is between 2.5% and 18.6%.

An approach to wide-field imaging of linear rail ground-based SAR in high squint multi-angle mode

Ground-based synthetic aperture radar(GB-SAR) has been successfully applied to the ground deformation monitoring.However, due to the short length of the GB-SAR platform, the scope of observation is largely limited. The practical applications drive us to make improvements on the conventional linear rail GB-SAR system in order to achieve larger field imaging. First, a turntable is utilized to support the rotational movement of the radar.Next, a series of high-squint scanning is performed with multiple squint angles. Further, the high squint modulation phase of the echo data is eliminated. Then, a new multi-angle imaging method is performed in the wave number domain to expand the field of view. Simulation and real experiments verify the effectiveness of this method.

Ground-based GPS Used in the Snow Depth Survey of Greenland

Snow cover is one of the important components of land cover,and it is necessary to accurately monitor the depth and coverage of snow cover.Using the GPS signal receiver data and the basic principle of snow depth detection based on GPS-MR technology,the snow depth of the three sites on the Greenland PBO network GLS1,GLS2,and GLS3 from 2012 to 2018 was obtained.The inversion snow depth is affected by site drift,which is a quite difference from the measured snow depth.Combined with the stable reference point,the velocity field distribution of Greenland Island and the U-direction component change value of the station can be obtained through GAMIT calculation.By analyzing the glacial flow and U-direction component,the influence of the site drift on the snow depth was deducted,and finally compared the corrected inversion snow depth and measured snow depth found that the two were better than before the correction,the results were significantly improved,and the consistency was good.The analysis of the experimental results showed that in extremely cold areas such as Greenland Island,affected by glaciers,the continuous,real-time,high-time resolution snow depth around the measured station obtained by ground-based GPS tracking stations has a large gap with the measured snow depth value,and the gap will gradually increase with time.By deducting the impact of glacier drift,the trend of the two is the same and the consistency is good.The correctness and feasibility of the application of ground-based GPS snow cover theory in the polar area further expand the application scope and practical value of ground-based GPS in snow monitoring.

MAX-DOAS and OMI Measurements of Tropospheric NO2 and HCHO over Eastern China

In this paper,we present long term observations of atmospheric nitrogen dioxide(NO2)and formaldehyde(HCHO)in Nanjing using a Multi-AXis Differential Optical Absorption Spectroscopy(MAX-DOAS)instrument.Ground based MAX-DOAS measurements were performed from April 2013 to February 2017.The MAX-DOAS measurements of NO2 and HCHO vertical column densities(VCDs)are used to validate OMI satellite observations over Nanjing.The comparison shows that the OMI observations of NO2 correlate well with the MAX-DOAS data with Pearson correlation coefficient(R)of 0.91.The comparison result of MAX-DOAS and OMI observations of HCHO VCD shows a good agreement with R of 0.75 and the slope of the regression line is 0.99.The age weighted backward propagation approach is applied to the MAX-DOAS measurements of NO2 and HCHO to reconstruct the spatial distribution of NO2 and HCHO over the Yangtze River Delta during summer and winter time.The reconstructed NO2 fields show a distinct agreement with OMI satellite observations.However,due to the short atmospheric lifetime of HCHO,the backward propagated HCHO data does not show a strong spatial correlation with the OMI HCHO observations.The result shows the MAX-DOAS measurements are sensitive to the air pollution transportation in the Yangtze River Delta,indicating the air quality in Nanjing is significantly influenced by regional transportation of air pollutants.

Pose Estimation of Space Targets Based on Model Matching for Large-Aperture Ground-Based Telescopes

With the development of adaptive optics and post restore processing techniques,large aperture ground-based telescopes can obtain high-resolution images(HRIs)of targets.The pose of the space target can be estimated from HRIs by several methods.As the target features obtained from the image are unstable,it is difficult to use existing methods for pose estimation.In this paper a method based on real-time target model matching to estimate the pose of space targets is proposed.First,the physicallyconstrained iterative deconvolution algorithm is used to obtain HRIs of the space target.Second,according to the 3D model,the ephemeris data,the observation time of the target,and the optical parameters of the telescope,the simulated observation image of the target in orbit is rendered by a scene simulation program.Finally,the target model searches through yaw,pitch,and roll until the correlation between the simulated observation image and the actual observation image shows an optimal match.The simulation results show that the proposed pose estimation method can converge to the local optimal value with an estimation error of about 1.6349°.

Time-varying baseline error correction method for ground-based micro-deformation monitoring radar

In recent years, ground-based micro-deformation monitoring radar has attracted much attention due to its excellent monitoring capability. By controlling the repeated campaigns of the radar antenna on a fixed track, ground-based micro-deformation monitoring radar can accomplish repeat-pass interferometry without a space baseline and thus obtain highprecision deformation data of a large scene at one time. However, it is difficult to guarantee absolute stable installation position in every campaign. If the installation position is unstable, the stability of the radar track will be affected randomly, resulting in time-varying baseline error. In this study, a correction method for this error is developed by analyzing the error distribution law while the spatial baseline is unknown. In practice, the error data are first identified by frequency components, then the data of each one-dimensional array(in azimuth direction or range direction) are grouped based on numerical distribution period, and finally the error is corrected by the nonlinear model established with each group.This method is verified with measured data from a slope in southern China, and the results show that the method can effectively correct the time-varying baseline error caused by rail instability and effectively improve the monitoring data accuracy of groundbased micro-deformation radar in short term and long term.

Ground-Based Cloud Using Exponential Entropy/Exponential Gray Entropy and UPSO

Objective and accurate classification model or method of cloud image is a prerequisite for accurate weather monitoring and forecast.Thus safety of aircraft taking off and landing and air flight can be guaranteed.Thresholding is a kind of simple and effective method of cloud classification.It can realize automated ground-based cloud detection and cloudage observation.The existing segmentation methods based on fixed threshold and single threshold cannot achieve good segmentation effect.Thus it is difficult to obtain the accurate result of cloud detection and cloudage observation.In view of the above-mentioned problems,multi-thresholding methods of ground-based cloud based on exponential entropy/exponential gray entropy and uniform searching particle swarm optimization(UPSO)are proposed.Exponential entropy and exponential gray entropy make up for the defects of undefined value and zero value in Shannon entropy.In addition,exponential gray entropy reflects the relative uniformity of gray levels within the cloud cluster and background cluster.Cloud regions and background regions of different gray level ranges can be distinguished more precisely using the multi-thresholding strategy.In order to reduce computational complexity of original exhaustive algorithm for multi-threshold selection,the UPSO algorithm is adopted.It can find the optimal thresholds quickly and accurately.As a result,the real-time processing of segmentation of groundbased cloud image can be realized.The experimental results show that,in comparison with the existing groundbased cloud image segmentation methods and multi-thresholding method based on maximum Shannon entropy,the proposed methods can extract the boundary shape,textures and details feature of cloud more clearly.Therefore,the accuracies of cloudage detection and morphology classification for ground-based cloud are both improved.

Constrained geometry analysis to resolve 3-D deformations from three ground-based radars

When multiple ground-based radars(GB-rads)are utilized together to resolve three-dimensional(3-D)deformations,the resolving accuracy is related with the measurement geometry constructed by these radars.This paper focuses on constrained geometry analysis to resolve 3-D deformations from three GB-rads.The geometric dilution of precision(GDOP)is utilized to evaluate 3-D deformation accuracy of a single target,and its theoretical equation is derived by building a simplified 3-D coordinate system.Then for a 3-D scene,its optimal accuracy problem is converted into determining the minimum value of an objective function with a boundary constraint.The genetic algorithm is utilized to solve this constrained optimization problem.Numerical simulations are made to validate the correctness of the theoretical analysis results.

基于MAX-DOAS的上海市区NO_(2)对流层柱浓度研究

二氧化氮(NO_(2))是大气中的主要污染物之一,在对流层和平流层大气化学中发挥关键作用,不仅参与对流层臭氧的催化形成,而且还有助于气溶胶的生成并导致酸雨等气候灾害,危害人体健康。人为源排放(工业,电厂、交通等排放)的NO_(2)占氮氧化物排放总量的大部分。传统的监测手段例如卫星遥感技术对对流层底部没有足够的敏感度,原位采样仪器则只能获得近地面的污染物浓度信息。近年来广泛使用的多轴差分吸收光谱技术(MAX-DOAS)不仅对近地面观测敏感,还拥有时间分辨率高,探测下限低,可以同时监测多种污染物等优点。为了实时监测上海市NO_(2)对流层柱浓度的变化特征,在上海市徐汇区搭设了地基MAX-DOAS仪器,进行了长期的持续观测。分析2019年6月至9月的MAX-DOAS观测数据,发现NO_(2)VCDs(垂直柱浓度)受交通排放影响显著,一般上午9:00左右达到峰值(1.56×10^(16)molec·cm^(-2)),随光照增强浓度降低明显,午后达到最低值(1.21×10^(16)molec·cm^(-2)),傍晚交通排放增强16:00以后浓度再次抬升。工作日早高峰期间的NO_(2)VCDs明显高于周末(高出约11.8%),而周末傍晚NO_(2)VCDs较工作日傍晚大幅上升。将MAX-DOAS观测结果与TORPOMI卫星观测数据对比发现,两个数据具有良好的一致性,相关性系数r为0.87。采用HYSPLIT后向轨迹模型对观测期间500 m高空气团输运后向轨迹进行聚类分析,发现上海市NO_(2)污染受沿海区域污染气团输送影响较大。研究表明,地基MAX-DOAS系统作为一种实时、快速、连续的大气监测手段,可以广泛应用于城市区域污染监测应用中。上海市对流层NO_(2)的观测研究为上海市大气污染防治提供了一定的数据支持。

MAX-DOAS and in-situ measurements of aerosols and trace gases over Dongying,China:Insight into ozone formation sensitivity based on secondary HCHO

This study presents a comprehensive overview of the atmospheric pollutants including Sulfur dioxide(SO_(2)),Nitrogen dioxide(NO_(2)),Formaldehyde(HCHO),Particulate Matter PM;PM_(10):diameter≤10μm,and PM_(2.5):diameter≤2.5μm,and Ozone(O_(3)),over Dongying(Shandong Province)from March-April 2018 and September-October 2019 by employing ground-based Multiple Axis Differential Optical Absorption Spectroscopy(MAX-DOAS)observations along with the in-situ measurements attained by the national air quality monitoring platform.The concentrations of SO_(2)and NO_(2)were under the acceptable level,while both PM_(2.5),and PM_(10)were higher than the safe levels as prescribed by national and international air quality standards.The results depict that 21%of the total observation days were found to be complex polluted days(PM_(2.5)>35μg/m^(3) and O_(3)>160μg/m^(3)).The secondary HCHO was used for accurate analysis of O_(3)sensitivity.A difference of 11.40%and 10%during March-April 2018 and September-October 2019 respectively in O_(3)sensitivity was found between HCHO_(total)/NO_(2)and HCHO_(sec)/NO_(2).The results indicate that primary HCHO have significant contribution in HCHO.O_(3)formation predominantly remained to be in VOC-limited and transitional regime during March-April 2018 and September-October 2019 in Dongying.These results imply that concurrent control of both NO_(x) and VOCs would benefit in ozone reductions.Additionally,the criteria pollutants(PM,SO_(2),and NO_(2))depicted strong correlations with each other except for O_(3)for which weak correlation coefficient was obtained with all the species.This study will prove to be baseline for designing of air pollution control strategies.

基于MAX-DOAS和TROPOMI对北京冬季对流层NO_(2)污染监测和对比分析

利用不同监测平台对大气环境污染进行监测时,不同遥感数据之间的对比验证以及协同观测是准确评估大气污染变化的关键。本文利用北京站点布置的多轴差分吸收光谱仪(MAX-DOAS)光谱仪,反演了2018年11月—2019年2月北京站点冬季的对流层NO_(2)垂直柱浓度,总结了北京冬季NO_(2)的日变化和月变化规律。研究中首先利用MAX-DOAS测量光谱结合DOAS反演算法获取不同时刻对流层NO_(2)垂直柱浓度,与TROPOMI过境时刻的NO_(2)遥测数据的变化趋势和相关性进行比较,并对卫星过境时地基站点不同的数据平均时间,和星—地间平均采样距离进行敏感性分析,同时将双因素方差分析方法(Two-way ANOVA)应用于评估风场对区域NO_(2)浓度变化的影响。结果显示北京地区11月的对流层NO_(2)平均浓度高于冬季其他月份,最大时均浓度可达到4.04×1016 molec·cm-2,且冬季各月份下午对流层平均NO_(2)浓度明显高于上午。利用TROPOMI和MAX-DOAS获得的对流层NO_(2)具有较好的相关性(r=0.88),其中2018年12月星—地观测相关性可达到0.96,但TROPOMI的NO_(2)浓度结果相对于地基MAX-DOAS观测结果均有不同程度的高估。同时星—地对比敏感性表明,在一定的采样范围内,随着平均时间和平均距离的增大,星—地NO_(2)浓度检测相关性均表现为明显的增高,其中相关性对采样距离的敏感性较大,而浓度相对偏差对采样时间敏感性较大,这为数据对比时的合理采样间隔选择提供参考。此外,通过风场分析发现风速及风速和风向的交互作用是导致北京地区NO_(2)浓度变化的重要因素之一。