Verifying Fossil-Fuel Carbon Dioxide Emissions Forecasted by an Artificial Neural Network with the GEOS-Chem Model

In this study, the authors developed an en- semble of Elman neural networks to forecast the spatial and temporal distribution of fossil-fuel emissions （ff） in 2009. The authors built and trained 29 Elman neural net- works based on the monthly average grid emission data （1979-2008） from different geographical regions. A three-dimensional global chemical transport model, God- dard Earth Observing System （GEOS）-Chem, was applied to verify the effectiveness of the networks. The results showed that the networks captured the annual increasing trend and interannual variation of ff well. The difference between the simulations with the original and predicted ff ranged from -1 ppmv to 1 ppmv globally. Meanwhile, the authors evaluated the observed and simulated north-south gradient of the atmospheric CO2 concentrations near the surface. The two simulated gradients appeared to have a similar changing pattern to the observations, with a slightly higher background CO2 concentration, - 1 ppmv. The results indicate that the Elman neural network is a useful tool for better understanding the spatial and tem- poral distribution of the atmospheric C02 concentration and ft.     

The distribution of chlorophyll a and its influencing factors in different regions of the Bering Sea

The distribution of chlorophyll a(Chl a) and its relationships with physical and chemical parameters in different regions of the Bering Sea were discussed in July 2010. The results showed the seawater column Chl a concentrations were 13.41–553.89 mg/m2 and the average value was 118.15 mg/m2 in the study areas. The horizontal distribution of Chl a varied remarkably from basin to shelf in the Bering Sea. The regional order of Chl a concentrations from low to high was basin, slope, outer shelf, inner shelf, and middle shelf. The vertical distribution of Chl a was grouped mainly from single-peak type in basin, slope, outer shelf, and middle shelf, where the deep Chl a maxima(DCM) layer was observed at 25–50 m, 30–35 m, 36–44 m, and 37–47 m, respectively. The vertical distribution of Chl a mainly had three basic patterns: standard single-peak type, surface maximum type, and bottom maximum type in the inner shelf. The analysis also showed that the transportation of ocean currents may control the distribution of Chl a, and the effects were not simple in the basin of the Bering Sea. There was a positive correlation between Chl a and temperature, but no significant correlation between Chl a and nutrients. The Bering Sea slope was an area deeply influenced by slope current. Silicate was the factor that controlled the distribution of Chl a within parts of the water in the slope. Light intensity was an important environmental factor in controlling seawater column Chl a in the shelf, where Chl a was limited by nitrate rather than phosphate within the upper water. Meanwhile, there was a positive relationship between Chl a and salinity. Algal blooms broke out at Sta. B6 of the southwestern St. Lawrence Island and Stas F6 and F11 in the middle of the Bering Strait.     

The Characteristics of Atmospheric Ice Nuclei Measured at Different Altitudes in the Huangshan Mountains in Southeast China简

The concentration of ice nuclei （IN） and the relationship with aerosol particles were measured and analyzed using three 5-L mixing cloud chambers and a static diffusion cloud chamber at three altitudes in the Huangshan Mountains in Southeast China from May to September 2011.The results showed that the mean total number concentration of IN on the highest peak of the Huangshan Mountains at an activation temperature （Ta） of-20℃C was 16.6 L-1.When the supersaturation with respect to water （Sw） and with respect to ice （Si） were set to 5％,the average number concentrations of IN measured at an activation temperature of-20℃C by the static diffusion cloud chamber were 0.89 and 0.105 L-1,respectively.A comparison of the concentrations of IN at three different altitudes showed that the concentration of IN at the foot of the mountains was higher than at the peak.A further calculation of the correlation between IN and the concentrations of aerosol particles of different size ranges showed that the IN concentration was well correlated with the concentration of aerosol particles in the size range of 1.2-20 μtm.It was also found that the IN concentration varied with meteorological conditions,such as wind speed,with higher IN concentrations often observed on days with strong wind.An analysis of the backward trajectories of air masses showed that low IN concentrations were often related to air masses travelling along southwest pathways,while higher IN concentrations were usually related to those transported along northeast pathways.     

The Southern Annular Mode (SAM) in PMIP2 simulations of the last glacial maximum

The increasing trend of the Southern Annular Mode （SAM） in recent decades has influenced climate change in the Southem Hemisphere （SH）.How the SAM will respond increased greenhouse gas concentrations in the future remains uncertain.Understanding the variability of the SAM in the past under a colder climate such as during the Last Glacial Maximum （LGM） might provide some understanding of the response of the SAM under a future warmer climate.We analyzed the changes in the SAM during the LGM in comparison to pre-industrial （PI） simulations using five coupled ocean-atmosphere models （CCSM,FGOALS,IPSL,MIROC,HadCM） from the second phase of the Paleoclimate Modelling Intercomparison Project （PMIP2）.In CCSM,MIROC,IPSL,and FGOALS,the variability of the simulated SAM appears to be reduced in the LGM compared to the PI simulations,with a decrease in the standard deviation of the SAM index.Overall,four out of the five models suggest a weaker SAM amplitude in the LGM consistent with a weaker SH polar vortex and westerly winds found in some proxy records and model analyses.The weakening of the SAM in the LGM was associated with an increase in the vertical propagation of Rossby waves in southern high latitudes.     

基于多源卫星遥感数据的中国2003年—2018年CO_(2)时空变化研究EI北大核心CSCD

本研究利用大气制图扫描成像吸收仪SCIAMACHY(Scanning Imaging Absorption Spectrometer for Atmospheric Chartography)和傅里叶变换光谱仪FTS(Fourier Transformation Spectrometer)卫星遥感传感器反演的CO_(2)产品,结合瓦里关地面站点观测的CO_(2)浓度数据进行验证,并对遥感数据进行校正,最后分析了2003年—2018年中国CO_(2)时空变化特征及其影响因素。结果表明,中国区域CO_(2)柱浓度呈近12个月周期变化且持续上升的趋势。2003年CO_(2)柱浓度年均值为374.4 ppm,2018年CO_(2)柱浓度年均值为413.7 ppm,16年间增加了39.3 ppm,约为10.51%,年均增长率为0.59%。中国区域大气CO_(2)柱浓度的月变化存在明显的时空差异,月变化呈现弦曲线变化,最小值和最大值分别出现在8和4月,2018年月平均大约分别为407.7 ppm和416.3 ppm。CO_(2)柱浓度的高值区主要出现在东部的亚热带和温带地区,2018年年平均最大可达417.9 ppm;最低值是在内蒙古北部,2018年平均约为409.5 ppm。从省级行政单元来看,2018年平均CO_(2)柱浓度最高和最低的省份是浙江省和青海省,分别约为417.8 ppm和412.1 ppm。中国2003年—2018年CO_(2)柱浓度在整个区域出现较大的增长,但是增长率在空间上存在明显的异质性。在空间上,2018年比2003年增长的数值在31.0—45.4 ppm之间,增长的百分比范围在8.9%—12.2%之间,增长较大的区域在高值区,最大增长出现在辽宁和吉林的交界处,约为12.2%;增长较小的区域出现在中国中部,最低的增长约为8.9%。     

泥质气源岩层内天然气扩散损失量评价——以黔南坳陷黄页1井九门冲组页岩为例

根据天然气扩散、物质平衡原理、烃浓度封闭机理和气源岩层之间扩散时间的相互匹配关系建立了评价泥质气源岩层内天然气扩散损失量的6种扩散模式以及不同模式下气源岩层天然气扩散损失量的计算方法,为定量评价部分烃浓度封闭期间气源岩层天然气扩散量、页岩气扩散量提供了可能。源岩层在受到部分烃浓度封闭期间的天然气扩散量,假设此期间不存在烃浓度封闭,则为源岩层的扩散气量与该期间上覆气源岩的扩散气量之差。利用所得模型对黔南坳陷黄页1井九门冲组页岩进行了实际应用,结果显示,黄页1井九门冲组页岩不考虑烃浓度封闭条件下的扩散气量远大于考虑烃浓度封闭条件下的扩散气量。在评价泥质气源岩层扩散量时如果存在烃浓度封闭作用,应加以考虑。     

区域土地利用影响地表CO2浓度异质性特征的动力学机制

本文综合应用高斯方程和拉姆齐模型,针对京津冀地区2000年以来10 km×10 km栅格尺度的地表CO₂浓度开展研究,分析了区域土地利用影响地表CO₂浓度异质性特征的动力学机制。研究发现：① 地表CO₂浓度与土地利用类型密切相关。2000—2018年京津冀地区CO₂浓度的高值区主要集中于经济较发达的快速城镇化地区;② 土地利用强度及土地利用效率上的时空分异为地表CO₂扩散提供了潜在的势能。京津冀地区地表CO₂排放及扩散存在明显的空间异质性,距离CO₂排放高值区越近,其相应的CO₂浓度越高并随时间推移及空间拓展呈逐步减小的态势;③ 京津冀地区在土地利用结构调整、格局优化及效率提升后,CO₂排放强度增幅明显减弱,其区域间的增幅差异也逐渐缩小。产业转型发展、土地利用格局优化、土地利用效率提高有效地抑制了京津冀地区地表CO₂排放强度的提升并促进了该区域的内涵式增长与高质量发展。     

2009—2011年大同市燃放烟花爆竹对可吸入颗粒物质量浓度的影响分析

利用2009—2011年春节期间大同市可吸入颗粒物(PM10)的质量浓度和气象资料,分析烟花爆竹燃放对空气质量的影响。结果表明:集中燃放时,如果有降雪,降雪对PM10的上升具有明显的抑制作用;无降雪时,风速仍是影响PM10的主要因素。除夕11:00—13:00、23:00—01:00,元宵节18:00—21:00,为PM10受烟花爆竹燃放影响最大的时段,其间PM10很高。集中燃放后,如果风速较大,PM10升高后很快降低,没有污染较小,而风速较小时,PM10升高较明显,对空气污染较严重。风速与PM10质量浓度为负相关关系,相关系数偏小。     

氢化物发生-原子荧光光谱法直接测定地球化学样品中痕量碲

采用硝酸-氢氟酸-高氯酸溶解样品,以Fe3 作减缓剂,不需分离富集,用氢化物发生-原子荧光光谱法直接测定地球化学样品中痕量碲.对测定介质、KBH4浓度、铁盐的作用等条件进行试验.方法检出限为0.0031μg/g,精密度(RSD,n=11)＜6.10%.方法用于国家一级地球化学标准物质中痕量碲的测定,结果与标准值一致.     

相对湿度和PM2.5浓度对大气能见度的影响研究:基于小时资料的多站对比分析

为了全面分析浙江省不同区域能见度变化基本特征及影响机理,基于杭州、宁波、温州3个国家基本气象站2013-2014年逐时能见度观测资料,比较分析了3市能见度变化的基本特征。发现3市不同等级能见度出现频率基本一致,随着能见度等级的提高,出现频率逐渐降低;从能见度的日变化来看,07时（北京时）前后最低,之后缓慢上升,14-15时达到最高,随后逐渐下降;全年有两个能见度较低时段,分别出现在12月-次年2月和5-6月;总体而言,宁波能见度最优,杭州和温州大体相当。功率谱分析结果表明,3市能见度均有显著的日周期,高频波段呈现出多个显著谱峰,低频波段存在若干显著谱峰。进一步开展机理分析,发现相对湿度和PM_2.5浓度是调制大气能见度的关键因子,相对湿度增大、PM_2.5浓度升高导致能见度降低。在同一相对湿度等级下,初始阶段能见度随PM_2.5浓度的升高迅速降低,到达“拐点”之后降低速率趋于缓慢。在同一PM_2.5浓度水平下,相对湿度越大,能见度越低,说明水汽对能见度也有重要影响。基于相对湿度和PM_2.5浓度两个因子,采用非线性拟合方案构建了大气能见度定量统计模型,总体而言模型拟合效果较好。最后针对研究中存在的不足和未来值得进一步发掘的科学问题进行了讨论。