A study of the validation of atmospheric CO_2 from satellite hyper spectral remote sensing

Three total column dry-air mole fractions of CO_2(XCO_2) products from satellite retrievals, namely SCIAMACHY, NIES-GOSAT, and ACOS-GOSAT, in the Northern Hemisphere were validated by ground data from the Total Carbon Column Observing Network(TCCON). The results showed that the satellite data have the same seasonal fluctuations as in the TCCON data, with maximum in April or May and minimum in August or September. The three products all underestimate the XCO2. The ACOS-GOSAT and the NIES-GOSAT products are roughly equivalent, and their mean standard deviations are 2.26 × 10^(-6)and 2.27 × 10^(-6)respectively. The accuracy of the SCIMACHY product is slightly lower, with a mean standard deviation of 2.91 × 10^(-6).

Optical remote sensing image characteristics of large amplitude convex mode-2 internal solitary waves:an experimental study

A series of experiments are designed to propose a new method to study the characteristics of convex mode-2internal solitary waves(ISWs)in optical remote sensing images using a laboratory-based optical remote sensing simulation platform.The corresponding wave parameters of large-amplitude convex mode-2 ISWs under smooth surfaces are investigated along with the optical remote sensing characteristic parameters.The mode-2 ISWs in the experimentally obtained optical remote sensing image are produced by their overall modulation effect on the water surface,and the extreme points of the gray value of the profile curve of bright-dark stripes appear at the same location as the real optical remote sensing image.The present data extend to a larger range than previous studies,and for the characteristics of large amplitude convex mode-2 ISWs,the experimental results show a second-order dependence of wavelength on amplitude.There is a close relationship between optical remote sensing characteristic parameters and wave parameters of mode-2 ISWs,in which there is a positive linear relationship between the bright-dark spacing and wavelength and a nonlinear relationship with the amplitude,especially when the amplitude is very large,there is a significant increase in bright-dark spacing.

Assessment of the State of Forests Based on Joint Statistical Processing of Sentinel-2B Remote Sensing Data and the Data from Network of Ground-Based ICP-Forests Sample Plots

The research was carried out on the territory of the Karelian Isthmus of the Leningrad Region using Sentinel-2B images and data from a network of ground sample plots. The ground sample plots are located in the studied territory mainly in a regular manner, laid and surveyed according to the ICP-Forests methodology with some additions. The total area of the sample plots is a small part of the entire study area. One of the objectives of the study was to determine the possibility of using the k-NN (nearest neighbor method) to assess the state of forests throughout the whole studied territory by joint statistical processing of data from ground sample plots and Sentinel-2B imagery. The data of the ground-based sample plots were divided into 2 equal parts, one for the application of the k-NN method, the second for checking the results of the method application. The systematic error in determining the mean damage class of the tree stands on sample plots by the k-NN method turned out to be zero, the random error is equal to one point. These results offer a possibility to determine the state of the forest in the entire study area. The second objective of the study was to examine the possibility of using the short-wave vegetation index (SWVI) to assess the state of forests. As a result, a close statistically reliable dependence of the average score of the state of plantations and the value of the SWVI index was established, which makes it possible to use the established relationship to determine the state of forests throughout the studied territory. The joint use and statistical processing of remotely sensed data and ground-based test areas by the two studied methods make it possible to assess the state of forests throughout the large studied area within the image. The results obtained can be used to monitor the state of forests in large areas and design appropriate forestry protective measures.

Using multi-satellite microwave remote sensing observations for retrieval of daily surface soil moisture across China

The objective of this study was to retrieve daily composite soil moisture by jointly using brightness temperature observations from multiple operating satellites for near real-time application with better coverage and higher accuracy.Our approach was to first apply the single-channel brightness radiometric algorithm to estimate soil moisture from the respective brightness temperature observations of the SMAP,SMOS,AMSR2,FY3B,and FY3C satellites on the same day and then produce a daily composite dataset by averaging the individual satellite-retrieved soil moisture.We further evaluated our product,the official soil moisture products of the five satellites,and the ensemble mean (i.e.,arithmetic mean) of the five official satellite soil moisture products against ground observations from two networks in Central Tibet and Anhui Province,China.The results show that our product outperforms the individual released products of the five satellites and their ensemble means in the two validation areas.The root mean square error (RMSE ) values of our product were 0.06 and 0.09 m3/m3 in Central Tibet and Anhui Province,respectively.Relative to the ensemble mean of the five satellite products,our product improves the accuracy by 9.1% and 57.7% in Central Tibet and Anhui Province,respectively.This demonstrates that jointly using brightness temperature observations from multiple satellites to retrieve soil moisture not only improves the spatial coverage of daily observations but also produces better daily composite products.

基于OCO-2卫星数据的中国CO_(2)浓度时空变化特征

大气CO_(2)浓度增加引起的全球变暖问题是国内外学者关注的热点议题,但对CO_(2)的监测一直存在较多的不确定性。利用2015—2022年OCO-2卫星观测的CO_(2)柱浓度混合比数据(XCO_(2)),基于克里金插值和标准差椭圆等方法,分析了中国CO_(2)浓度时空分布与变化特征,有以下3个结论。1)基于OCO-2卫星数据的XCO_(2)数据集精度较高,与地面监测站(瓦里关站、鹿林站)观测结果的均方根误差仅为1.75 ppm和1.58 ppm,相关系数分别为0.91和0.96。2)年际上,2015—2022年中国年均XCO_(2)由399.52 ppm增至417.64 ppm,年均增速为2.56 ppm/a,高于过去10年全球CO_(2)浓度平均增速(2.06 ppm/a),但在2019年之后XCO_(2)增速呈下降趋势。季节上,XCO_(2)具有明显的季节变化特征,春季XCO_(2)最高,夏季最低。3)空间分布上,XCO_(2)表现出东部高,西部、东北地区低的空间分布特征。XCO_(2)浓度高值区域集中在京津冀和长三角等城市群。中国东北、西南地区XCO_(2)增速较快,高于华东、华南等经济发达地区。

Study on the Correlation Between Chlorophyll Maximum and Remote Sensing Data

Based on the in situ optical measurements in the Bohai Sea of China, which belongs to a typical case-2 water area, we studied the characteristics of DCM (deep chlorophyll maximum) such as its spatial distribution, vertical profile, etc. We found that when the depth of the chlorophyll maximum is comparatively small, even in turbid coastal water regions, there is always a good correlation between the concentrations of chlorophyll maximum and the satellite-received signals in blue-green spectral bands; the correlation is even better than that between the surface chlorophyll concentrations and the satellite-received signals. The strong correlation existing even in turbid coastal water regions indicates that an ocean color model to retrieve the concentration of DCM can be constructed for coastal waters if a comprehensive knowledge of the vertical distribution of chlorophyll concentration in the Bohai Sea of China is available.

A new strategy for ionospheric remote sensing using the 130.4/135.6 nm airglow intensity ratios

We demonstrate here that global-scale determination of a key ionospheric parameter,the peak height of the F_(2)region(h_(m)F_(2)),can be obtained by making a simple ratio measurement of the atomic oxygen 130.4 and 135.6 nm emissions in the far-ultraviolet nightglow with a nadir-viewing system such as a pair of photometers suitable for flight on a CubeSat.We further demonstrate that measurements from an altitude that is within the typical range of nighttime h_(m)F_(2)250−450 km can provide the ratios that are needed for retrieval of the h_(m)F_(2).Our study is conducted mostly through numerical simulations by using radiative transfer models of the two emissions coupled with empirical models of the atmosphere and ionosphere.Modeling results show that the relationship between the h_(m)F_(2)and the intensity ratio is sensitive to the altitude from which the emissions are observed,primarily because of the distinctly different degrees of resonant scattering of the two emissions in the atmosphere.A roughly quadratic relationship can be established for observations from an orbit of~400 km,which enables h_(m)F_(2)retrieval.Parametric analysis indicates that the relationship can be affected by the ambient atmospheric conditions through resonant scattering and O2 absorption.For typical nighttime conditions with h_(m)F_(2)250−450 km,retrieval of the h_(m)F_(2)from synthetic observations shows that the typical errors are only a few kilometers(up to~20 km),depending on the accuracy of the ambient conditions predicted by the empirical models.Our findings pave the way for use of the 130.4/135.6 nm intensity ratios for global-scale monitoring of the nighttime ionosphere at mid to low latitudes.

Spectral Analysis of Water Reflectance for Hyperspectral Remote Sensing of Water Quailty in Estuarine Water

Hyperspectral remote sensing offers an effective approach for frequent, synoptic water quality measurements over a large spatial extent. However, the optical complexity of case 2 water makes the water quality monitoring by remote sensing in estuarine water a challenge. The prime objective of this study was to develop algorithms for hyperspectral remote sensing of water quality based on in situ spectral measurement of water reflectance. In this study, water reflectance spectra R(λ) were acquired by a pair of Ocean Optic 2000 spectroradiometers during the summers from 2008 to 2011 at Patuxent River, a tributary of Chesapeake Bay, USA. Simultaneously, concentrations of chlorophyll a and total suspended solids (TSS), as well as absorption of colored dissolved organic matter (CDOM) were measured. Empirical models that based on spectral features of water reflectance generally showed good correlations with water quality parameters. The retrieval model that using spectral bands at red/NIR showed a high correlation with chlorophyll a concentration (R2 = 0.81). The ratio of green to blue spectral bands is the best predictor for TSS (R2 = 0.75), and CDOM absorption is best correlated with spectral features at blue and NIR regions (R2 = 0.85). These empirical models were further applied to the ASIA Eagle hyperspectral aerial imagery to demonstrate the feasibility of hyperspectral remote sensing of water quality in the optical complex estuarine waters.

INFLUENCE OF Pr_6O_(11) ON THE GAS SENSING CHARACTERISTICS OF SnO_2 SEMICONDUCTOR

This paper is to discuss the sensing characteristics of SnO_2 semiconductor components in which Pr_6O_(11) is added.When experimenting under 11 gases of CH_3COCH_3,C_2H_5OH.C_6H_5CH_3,H_2,NH_3,CO, CO_2 CH_4,C_4H_10,n—C_6H_(14)and n—C_7H_(16),we find that the components have selectivity to CH_3COCH_3, C_2H_5OH and that the ideal amount of Pr_6O_(11) in the components is about I.Owt%.The experiments also show that with the increase of the amount of Pr_6O_(11),the ideal working temperature,the response and restoration time decrease.

Preparation of porous α-Fe_2O_3-supported Pt and its sensing performance to volatile organic compounds

Porous α-Fe2O3 was synthesized by a simple hydrothermal treatment of FeC13 aqueous solution followed by a calcination process. In the synthesis of porous α-Fe2O3, no templates or pore-directing agents were used. The as-prepared porous α-Fe2O3 was further employed as a support for loading Pt nanoparticles. The gas sensing performance of the obtained porous α-Fe2O3-supported Pt to VOCs was investigated. The sensor presented a high response and fast response-recovery characteristic to several VOCs including acetone, ether, methanol, ethanol, butanol and hexanol. Meanwhile, it exhibited a much higher response than the pure α-Fe2O3 at the operating temperature of 260 ℃. The enhanced sensing properties may be related to the unique porous structure of the α-Fe2O3 support and the promoting effect of active Pt nanoparticles for the sensing reactions.

常见运动系软组织损伤性疼痛O_2-O_3治疗临床观察

目的通过对8种常见运动系软组织损伤性疼痛的O2-O3局部浸润治疗的观察,评价短期和中远期疗效.同时总结了本治疗组经验。方法采用国产JZ-100型臭氧治疗仪,医用纯氧为原料,制备浓度35～40mg/LO2-O3混合气体,5ml一次性注射器分次抽取。根据每种疾病的病理解剖特征,分别采用不同的浸润注射方法,4次为一疗程,每次间隔3日。结果8种疾病平均随访2月优良率达85%左右,6个月优良率70%左右。结论准确的疼痛点和解剖层次内浸润,疗效是肯定的,可反复多次应用,没有激素类药物副作用。

ART Based Reliable Method for Prediction of Agricultural Land Changes Using Remote Sensing

This paper focuses on prediction of change in agricultural lands by using ART2 algorithm. The existing method used ENVI and ARCGIS software to predict the changes in land, which showed less accuracy due to human errors. To overcome this user friendly GUI based ART2 algorithm has been developed in java to obtain more accuracy in prediction of changes in land. The input is satellite temporal images of the years 1990 and 2014. By using the ART2 algorithm, the input images of the years 1990 and 2014 are classified, where the features are identified to form cluster. The clustered image is given as input and pixel to pixel comparison method in ART2 is implemented in java, for detecting the changes in agricultural lands. The comparison results of ENVI and ARCGIS and GUI based ART2 with in situ data show that the prediction of changes in agricultural land is more accurate in the case of GUI based ART2 implementation.

Big geochemical data through remote sensing for dynamic mineral resource monitoring in tailing storage facilities

Evolution in geoscientific data provides the mineral industry with new opportunities.A direction of geochemical data generation evolution is towards big data to meet the demands of data-driven usage scenarios that rely on data velocity.This direction is more significant where traditional geochemical data are not ideal,which is the case for evaluating unconventional resources,such as tailing storage facilities(TSFs),because they are not static due to sedimentation,compaction and changes associated with hydrospheric and lithospheric processes(e.g.,erosion,saltation and mobility of chemical constituents).In this paper,we generate big secondary geochemical data derived from Sentinel-2 satellite-remote sensing data to showcase the benefits of big geochemical data using TSFs from the Witwatersrand Basin(South Africa).Using spatially fused remote sensing and legacy geochemical data on the Dump 20 TSF,we trained a machine learning model to predict in-situ gold grades.Subsequently,we deployed the model to the Lindum TSF,which is 3 km away,over a period of a few years(2015-2019).We were able to visualize and analyze the temporal variation in the spatial distributions of the gold grade of the Lindum TSF.Additionally,we were able to infer extraction sequencing(to the resolution of the data),acid mine drainage formation and seasonal migration.These findings suggest that dynamic mineral resource models and live geochemical monitoring(e.g.,of elemental mobility and structural changes)are possible without additional physical sampling.

基于O2-O2吸收的非相干宽带腔增强吸收光谱浓度反演方法研究

针对传统非相干宽带腔增强吸收光谱浓度反演方法的定量结果易受镜片反射率标定误差的影响问题,提出了一种基于测量大气O2-O2吸收的浓度反演方法.该方法是将非相干宽带腔增强吸收光谱技术的光学增强腔等效成吸收光程不随波长变化的多次反射池,首先根据测得的宽带腔增强大气吸收谱和参考谱计算出光学厚度,并应用差分光学吸收光谱算法拟合修正后的气体吸收截面到光学厚度,反演得到大气中O2-O2以及被测气体的柱浓度,然后根据O2-O2在大气中的含量已知且相对稳定这一特性,确定出等效多次反射池的吸收光程,最后从被测气体的柱浓度中扣除吸收光程信息得到被测气体的浓度值.以监测大气中NO2实验为例,应用该方法在454—487 nm波段反演得到了大气NO2的浓度(1—30 ppbv范围内),并将反演结果与传统浓度反演方法的结果进行了对比,发现两者的不一致性在7%以内.实验结果表明,非相干宽带腔增强吸收光谱技术可以利用大气O2-O2的吸收来定量其他被测气体的浓度,而且定量结果对镜片反射率的标定误差不敏感.

基于卫星遥感的中国人为CO_(2)与大气污染物排放协同关系

基于多源卫星遥感数据和大气输送模型研究我国人为CO_(2)与大气污染物(NO_(2)和CO)排放协同关系以及新冠疫情管控期间污碳排放变化特征.结果表明:高人为CO_(2)排放对应高浓度的NO_(2)和CO排放,以省级行政区为单位的2018~2020年非生长季XCO_(2)异常与XNO_(2)的相关性(r=0.79)高于与XCO的相关性(r=0.61),且高人为CO_(2)排放地区燃烧排放效率更高;2020年2月(疫情管控期)我国XCO_(2)异常、XNO_(2)、XCO下降的区域范围为2019年2月(疫情同比期)面积的50%、70%和49%,2020年2月XCO_(2)异常与XNO_(2)的相关性(r=0.71,P<0.01)高于2019年2月(r=0.59,P<0.01),而XCO_(2)异常与XCO的相关性(r=0.44,P<0.01)低于2019年2月(r=0.68,P<0.01);受大气输送的影响,2020年2月京津冀受西南方向人为排放地区输送的影响高于2019年2月,而长三角受北部长距离输送的影响降低,珠三角受大气输送的影响最小.研究结果表明卫星遥感可有效用于区域污碳协同排放时空变化特征监测.

用I_p作为N_2O_4-O_3硝化取代芳烃的定位判据

利用前沿轨道理论及N2O4 O3硝化芳烃的机理推导出取代芳烃第一电离能与取代基定位方向之间关系,用第一电离能IP的大小判断N2O4 O3硝化各种取代芳烃过程中NO2基团所取代的位置,提出了判断取代芳烃中取代基是对位定位基还是间位定位基的判据,此判据与实验结果相一致。

基于OCO-2遥感数据的新疆维吾尔自治区大气XCO_(2)空间化研究

二氧化碳(CO_(2))是导致全球变暖最主要的温室气体,掌握准确的CO_(2)空间分布信息可以有效评估碳减排成效,对于推进碳达峰、碳中和工作具有重要意义。相比站点观测,碳卫星能够获取大尺度的CO_(2)分布信息,但是由于其幅宽较窄以及云覆盖的影响,大气CO_(2)卫星遥感数据存在大量缺值区域,不能获得空间连续的大气CO_(2)分布。以新疆维吾尔自治区为研究区,基于2019年OCO-2卫星大气二氧化碳柱平均干空气混合比(XCO_(2))数据,结合气温、地形、植被、大气NO_(2)浓度等相关变量,综合对比了多元线性回归(MLR)、地理加权回归(GWR)、支持向量机(SVR)、随机森林(RF)、极端梯度提升树(XGBoost)和极端随机树(ERT)等方法在生成大气XCO_(2)空间连续数据中的表现。交叉验证结果表明,RF、XGBoost和ERT这3种集成学习模型精度明显优于SVR、GWR和MLR模型,其中ERT模型精度最高,决定系数R^(2)为0.748,平均绝对误差σ_(MAE)为0.489×10^(-6)。基于ERT模型生成了新疆2019年逐月大气XCO_(2)空间连续数据,该地区大气XCO_(2)空间差异和季节变化都很明显。在空间分布格局上总体呈现与地形“三山夹两盆”相似的空间分布特征,裸地XCO_(2)年均值最高,林地和草原的XCO_(2)年均值最低;季节变化特征与植被生长周期相似,春冬季浓度较高,夏秋季浓度较低,最高值出现在4月,最低值出现在8月,不同土地覆盖类型的大气XCO_(2)季节变化与全区域类似,其中草原和林地的季节差异最大,裸地季节差异最小。该研究为基于碳卫星遥感数据生成时空连续的大尺度XCO_(2)数据提供了参考和借鉴。

N_2O_4-O_3硝化取代芳烃时取代基上的P轨道的邻位协助作用

对N2 O4 O3 硝化取代芳烃进行广泛的研究 ,发现其产物的异构体分布与传统的混酸硝化产物的异构体分布有很大差别 ,并对造成这种差别的原因进行了分析。分析表明 ,取代基上的P轨道的邻位协助作用是主要因素 。

衍生气相色谱法测定O,O-二乙基-O-(2-氯-4-溴)苯基硫代磷酸酯

建立了O,O-二乙基-O-(2-氯-4-溴)苯基硫代磷酸酯的衍生气相色谱法。方法的标准偏差为0.29、变异系数为0.30%、平均回收率为99.32%,表明其精密度和准确度良好,完全可用于O,O-二乙基-O-(2-氯-4-溴)苯基硫代磷酸酯的分析。

Fe^(2＋)诱导H_2O_2-O_3氧化邻苯二甲酸二甲酯研究

采用Fe2+诱导H2O2-O3,进行了内分泌干扰物邻苯二甲酸二甲酯(DMP)的降解试验。结果表明,Fe2+的存在消除了H2O2对臭氧的抑制作用,并使得H2O2-O3对DMP的氧化作用提高了31.75个百分点。当溶液DMP的初始质量浓度为50 mg.L-1、温度为60℃、初始pH为10、H2O2投加量为49 mmol.L-1、O3投加量为1.82 g.h-1、Fe2+投加量为0.72 mmol.L-1时,反应45 min的条件下,Fe2+-H2O2-O3对DMP的去除率可达到78.32%。