2007和2008年夏季北京奥运馆大气PM10与PM2.5质量浓度变化特征

为了监测北京奥运主场馆附近大气颗粒物的污染状况以及评估奥运污染源减排措施对北京大气颗粒物质量浓度变化的影响,利用颗粒物在线监测仪器TEOM于2007年和2008年夏季,在奥运主场馆附近的中国科学院遥感应用研究所办公楼楼顶对大气颗粒物PM₁₀和PM_2.5进行了连续同步观测。结果表明,2007年夏季监测点附近大气PM₁₀与PM_2.5质量浓度的平均值分别为153.9和71.2μg·m^-3,而2008年夏季PM₁₀与PM_2.5质量浓度的平均值分别为85.2和52.8μg·m^-3。与奥运前一年同时段相比,奥运时段大气PM₁₀和PM_2.5的质量浓度分别下降44.5%和25.1%。对比分析奥运前后的2次典型污染过程发现,空气相对湿度的增加和偏南气流输送的共同影响易造成大气颗粒物的累积增长,而降雨的湿清除作用和偏北气流则会使大气颗粒物浓度迅速降低。在相近的气象条件下,奥运前后的污染过程中,大气细粒子的日均增长速率分别为25.1和13.9μg·m^-3·d^-1,而大气粗粒子的日均增长速率分别为20.8和2.2μg·m^-3·d^-1,奥运时段污染累积过程中大气粗、细粒子的增长速率分别显著低于和略低于奥运前同时段污染过程中颗粒物的增长速率。污染源减排措施的实施是奥运期间大气颗粒物质量浓度降低的主要原因,从控制效果来看,奥运期间实施的污染源减排措施对大气粗粒子的控制效果明显好于大气细粒子。     

基于CBERS的黄河湿地生物量反演研究

本研究以黄河湿地郑州段为研究区,利用RS与GIS技术,基于2009年5月7日获得的CBERS 2B卫星CCD多光谱遥感影像和地面实测植被生物量信息,采用回归算法构建反演模型,经对比分析得到最优计算模型。结果表明,反演模型计算精度达到86.32%,利用CBERS 2B卫星CCD多光谱遥感影像可满足植被生物量的反演需要。     

基于全极化SAR影像的舰船目标检测算法研究

介绍了基于星载极化SAR影像的舰船目标检测的处理流程,针对基于不同杂波模型的CFAR检测法和基于相干信息的2L-IHP检测法,分析实现了瑞利分布、Gauss分布、韦布尔分布、对数正态分布,四种常用杂波分布模型的CA-CFAR检测法,通过实验检测海面舰船目标,发现这四种杂波模型针对不同海况有着不同的适应性,其检测效果也大不相同。而2L-IHP检测法不依赖于海杂波模型,通过子孔径相干提高目标和背景之间的对比度,实验结果表明,该方法能大幅提高海面舰船目标的检测概率。     

Modeling Methane Emissions from Paddy Rice Fields under Elevated Atmospheric Carbon Dioxide Conditions

Methane(CH4 ) emissions from paddy rice fields substantially contribute to the dramatic increase of this greenhouse gas in the atmosphere.Due to great concern about climate change,it is necessary to predict the effects of the dramatic increase in atmospheric carbon dioxide(CO2 ) on CH4 emissions from paddy rice fields.CH4MOD 1.0 is the most widely validated model for simulating CH4 emissions from paddy rice fields exposed to ambient CO2(hereinafter referred to as aCO2 ).We upgraded the model to CH4MOD 2.0 b...     

CO2 Flux Estimation by Different Regression Methods from an Alpine Meadow on the Qinghai-Tibetan Plateau

CO2 efflux was estimated using different regression methods in static chamber observation from an alpine meadow on the Qinghai-Tibetan Plateau. The CO2 efflux showed a seasonal pattern, with the maximun flux occurring in the middle of July. The temperature sensitivity of CO2 efflux (Q10> was 3.9, which was at the high end of the range of global values. CO2 emissions calculated by linear and nonlinear regression were significantly different (p<0.05). Compared with the linear regression, CO2 emissions calculated by exponential regression and quadratic regression were 12.7% and 11.2% larger, respectively. However, there were no significant differences in temperature sensitivity values estimated by the three methods. In the entire growing season, the CO2 efflux estimated by linear regression may be underestimated by up to 25% compared to the real CO2 efflux. Consequently, great caution should be taken when using published flux data obtained by linear regression of static chamber observations to estimate the regional CO2 flux in alpine meadows on the Qinghai-Tibetan Plateau.     

Gap Filling and Quality Assessment of CO2 and Water Vapour Fluxes above an Urban Area with Radial Basis Function Neural Networks

Vertical turbulent fluxes of water vapour, carbon dioxide, and sensible heat were measured from 16 August to the 28 September 2006 near the city centre of Münster in north-west Germany. In comparison to results of measurements above homogeneous ecosystem sites, the CO₂ fluxes above the urban investigation area showed more peaks and higher variances during the course of a day, probably caused by traffic and other varying, anthropogenic sources. The main goal of this study is the introduction and establishment of a new gap filling procedure using radial basis function (RBF) neural networks, which is also applicable under complex environmental conditions. We applied adapted RBF neural networks within a combined modular expert system of neural networks as an innovative approach to fill data gaps in micrometeorological flux time series. We found that RBF networks are superior to multi-layer perceptron (MLP) neural networks in the reproduction of the highly variable turbulent fluxes. In addition, we enhanced the methodology in the field of quality assessment for eddy covariance data. An RBF neural network mapping system was used to identify conditions of a turbulence regime that allows reliable quantification of turbulent fluxes through finding an acceptable minimum of the friction velocity. For the data analysed in this study, the minimum acceptable friction velocity was found to be 0.15 m s⁻¹. The obtained CO₂ fluxes, measured on a tower at 65 m a.g.l., reached average values of 12 μmol m⁻² s⁻¹ and fell to nighttime minimum values of 3 μmol m ⁻² s⁻¹. Mean daily CO₂ emissions of 21 g CO₂ m⁻²d ⁻¹ were obtained during our 6-week experiment. Hence, the city centre of Münster appeared to be a significant source of CO₂. The half-hourly average values of water vapour fluxes ranged between 0.062 and 0.989 mmol m⁻² s⁻¹and showed lower variances than the simultaneously measured fluxes of CO₂.     

Investigating a Hierarchy of Eulerian Closure Models for Scalar Transfer Inside Forested Canopies

Modelling the transfer of heat, water vapour, and CO₂ between the biosphere and the atmosphere is made difficult by the complex two-way interaction between leaves and their immediate microclimate. When simulating scalar sources and sinks inside canopies on seasonal, inter-annual, or forest development time scales, the so-called well-mixed assumption (WMA) of mean concentration (i.e. vertically constant inside the canopy but dynamically evolving in time) is often employed. The WMA eliminates the need to model how vegetation alters its immediate microclimate, which necessitates formulations that utilize turbulent transport theories. Here, two inter-related questions pertinent to the WMA for modelling scalar sources, sinks, and fluxes at seasonal to inter-annual time scales are explored: (1) if the WMA is to be replaced so as to resolve this two-way interaction, how detailed must the turbulent transport model be? And (2) what are the added predictive skills gained by resolving the two-way interaction vis-à-vis other uncertainties such as seasonal variations in physiological parameters. These two questions are addressed by simulating multi-year mean scalar concentration and eddy-covariance scalar flux measurements collected in a Loblolly pine (P. taeda L.) plantation near Durham, North Carolina, U.S.A. using turbulent transport models ranging from K-theory (or first-order closure) to third-order closure schemes. The multi-layer model calculations with these closure schemes were contrasted with model calculations employing the WMA. These comparisons suggested that (i) among the three scalars, sensible heat flux predictions are most biased with respect to eddy-covariance measurements when using the WMA, (ii) first-order closure schemes are sufficient to reproduce the seasonal to inter-annual variations in scalar fluxes provided the canonical length scale of turbulence is properly specified, (iii) second-order closure models best agree with measured mean scalar concentration (and temperature) profiles inside the canopy as well as scalar fluxes above the canopy, (iv) there are no clear gains in predictive skills when using third-order closure schemes over their second-order closure counterparts. At inter-annual time scales, biases in modelled scalar fluxes incurred by using the WMA exceed those incurred when correcting for the seasonal amplitude in the maximum carboxylation capacity (V _{cmax, 25}) provided its mean value is unbiased. The role of local thermal stratification inside the canopy and possible computational simplifications in decoupling scalar transfer from the generation of the flow statistics are also discussed.

“The tree, tilting its leaves to capture bullets of light; inhaling, exhaling; its many thousand stomata breathing, creating the air”. Ruth Stone, 2002, In the Next Galaxy

     

基于SCIATRAN模型的二氧化氮DOAS 反演敏感性试验

气溶胶和地表反照率是影响星载SCIAMACHY仪器观测数据定量遥感NO2大气柱总量的2个主要因子.文中利用高光谱分辨率大气辐射传输模型SCIATRAN,在考虑分子吸收和气溶胶多次散射影响基础上,精确模拟了气溶胶、地表反照率和NO2气体浓度变化对差分处理前后卫星反射光谱的影响,并定义影响因子f,对3个模拟参数进行综合评价.结果表明:(1)通过剔除卫星反射光谱中慢变光谱变化成分,DOAS方法明显降低了气溶胶和地表反照率对卫星反射光谱的影响;(2)差分处理前,3个模拟参数的影响强弱依次为地表反照率、气溶胶和NO2浓度;而差分处理后,3个模拟参数的影响强弱依次为NO2浓度、地表反照率和气溶胶.在影响趋势上,气溶胶和地表反照率很相似,均体现为宽带效应,在440-450 nm内有水汽强吸收和多次散射复杂相互作用导致的较大峰值;NO2浓度变化对差分处理前后的光谱都呈现气体吸收结构的影响特性;(3)由于吸收和散射相互作用等因素的影响,在基于卫星观测的差分光谱中仍然残留有气溶胶和地表反照率的误差,地表反照率约占18.6%,气溶胶约占6.2%.因此,当前SCIAMACHY遥感的NO2产品在中国区域浓度偏高,需要对气溶胶和地表反照率进行二次精细化的订正.