基于探采对比的煤层瓦斯含量分析及预测

针对新建矿井地勘瓦斯含量测值偏低和井下实测瓦斯含量较少的特点,结合工程和科研实践,提出了利用大量的工作面瓦斯涌出量反演煤层原始瓦斯含量技术和基于探采对比的煤层瓦斯含量预测方法。以邹庄井田32煤层为研究对象,在考虑瓦斯抽采情况下计算3204工作面瓦斯涌出量,并反演该工作面煤层原始瓦斯含量。通过对比采掘过程中获得的瓦斯含量和地勘瓦斯含量,得到不同钻孔深度时的地勘瓦斯含量修正系数,并采用瓦斯地质研究方法对32煤层分3个单元进行瓦斯含量预测。结果表明:32煤层瓦斯含量整体呈现"东部大于西部,北部大于南部"的规律,与临近矿井具有相似的瓦斯赋存规律。这表明利用探采对比的方法预测煤层瓦斯含量是可靠的。     

外浮顶罐充氮管网设计及有效性试验验证

为了预防外浮顶罐密封圈雷击火灾,提出在密封圈内充入氮气的保护方法.将安全含氧量作为充氮的惰化目标,对外浮顶罐充氮管网进行设计,并通过试验来验证充氮管网的有效性.试验得到了充氮流量、进出气孔数量及管径与有效充氮时间的关系.若以142 m3/h的流量对容量为10×104 m3的外浮顶罐密封圈内充氮,则46.5 min内可以达到充氮惰化目标.雷电预警时间为60 ～ 90 min的条件下,充氮时间小于预警时间,表明所设计的管网是有效的.     

Wood carbon content of tree species in Eastern China: interspecific variability and the importance of the volatile fraction

Data on the mass density and carbon content of tree organs, and in particular stem wood, are essential for accurate assessments of forest carbon sequestration. However most available data, including that for East Asia, has neglected the volatile C fraction. Wood samples were collected and assayed for C content from 14 native tree species in Jilin Province, NE China. C content showed statistically significant variation among species, ranging from 48.4% to 51.0%. The volatile C fraction was non-negligible, averaging 2.2%, and showed high variation among species. As found in prior studies, wood C content was appreciably higher in conifer than hardwood (angiosperm) species (50.8+/-0.1% vs. 49.5+/-0.2%, respectively). Wood carbon density (gC/cm(3)) showed very high inter-specific variation, due mainly to differences in wood specific gravity. Our analyses, in conjunction with recently published data from North America, indicate a global mean value of 47.5+/-0.5% wood C content exclusive of volatile C; the widely used 50% figure corresponds more closely to total wood C inclusive of the volatile fraction. Failure to include volatile C or to use species- or higher-taxon-specific C content values in forest C assessments is likely to introduce biases on the order approximately 4-6%. In addition, the stocks and flows of the volatile C fraction in wood are in themselves an important and sorely neglected aspect of forest C processes likely to be strongly impacted by harvests and other management practices.     

基于内容分析法的河流健康内涵及表征

运用内容分析法对近10~15年中外文献中有影响力的36个河流健康概念进行分析,经过样本选取、指标提取、量化处理等过程提炼出最频繁出现的能代表其内涵的6个标准,即：维持结构完整性、自然生态功能发挥、满足人类社会合理需求、处于良好状态、河流管理工具和目标、建立河流基准状态。基于此,对河流健康概念进行了重新架构：河流健康是指河流生态系统特定的良好状况,可以作为河流基准状态以及河流管理的目标,在这一状态下,河流生态系统能够维持其生态系统结构完整性,充分发挥其自然生态功能,并满足人类社会合理需求,提供相应的社会服务功能。通过对30个有关河流健康表征指标及评价方法的文献进行分析,识别生物指标、水质参数、形态结构、河床底质、水文条件以及河岸带状况等是目前使用最广泛的6个指标,指出河流健康的表征指标及评价标准应根据区域特征、人类活动影响以及功能定位而有所差异。     

土壤有机质含量测定方法的改进研究

通过研究改进了土壤有机质含量的测定方法。首先称取适量土壤置于长管消解系统中进行消解,然后采用全自动电位滴定仪进行滴定,直接获得土壤的有机质含量。使用该方法测定的土壤标准样品的有机质含量均在保证值以内,同时对实际样品进行精密度测试,得到相对标准偏差为1．03％。该方法降低了土壤有机质含量检测的实验成本,减少了环境污染,同时提高了实验数据的准确度与精密度,值得推广。     

Sewage sludge disintegration by high-pressure homogenization: A sludge disintegration model

High-pressure homogenization (HPH) technology was applied as a pretreatment to disintegrate sewage sludge. The effects of homogenization pressure, homogenization cycle number, and total solid content on sludge disintegration were investigated. The sludge disintegration degree (DDCOD), protein concentration, and polysaccharide concentration increased with the increase of homogenization pressure and homogenization cycle number, and decreased with the increase of sludge total solid (TS) content. The maximum DDCOD of 43.94% was achieved at 80 MPa with four homogenization cycles for a 9.58 g/L TS sludge sample. A HPH sludge disintegration model of DD_COD= kN^aP^b was established by multivariable linear regression to quantify the effects of homogenization parameters. The homogenization cycle exponent a and homogenization pressure exponent b were 0.4763 and 0.7324 respectively, showing that the effect of homogenization pressure (P) was more significant than that of homogenization cycle number (N). The value of the rate constant k decreased with the increase of sludge total solid content. The specific energy consumption increased with the increment of sludge disintegration efficiency. Lower specific energy consumption was required for higher total solid content sludge.     

成都市典型非道路工程机械排气烟度分析

采用不透光烟度计采集了成都市典型工程机械(挖掘机、装载机、叉车和压路机)排气烟度,研究了机械功率对其活动水平(燃油消耗量和年均工作时间)的影响,同时也研究了机械发动机构造和机械排放标准对其排气烟度的影响;同时,采用氮硫测定仪分析了机械油品硫含量,研究了硫含量对其排气烟度的影响.试验结果表明:机械功率越大的工程机械,燃油消耗量和年均工作时间数越高.成都典型工程机械排气烟度排放水平最低的为装载机,最高的为压路机;同时,超高排放装载机与叉车的占比较高.工程机械排气烟度受机械发动机排量、机械发动机构造、机械发动机排放标准和机械用油的综合影响,通过对工程机械装配电控发动机、提高原机排放标准和使用低硫燃油均能直观反映出机械排气烟度不同程度的改善.此外,油品中硫含量越高,机械排气烟度越大.     

闽江口秋茄红树林凋落物产量及分解动态

于2017年以闽江口粗芦岛秋茄(Kandelia obovata)红树林为研究对象,分别采用凋落物收集框和分解袋法,研究秋茄凋落物产量及其碳(C)、氮(N)、磷(P)含量月动态及凋落叶分解过程中C、N、P含量与水解酶活性.结果表明:①秋茄凋落物年产量为618.79 g·m~(-2)·a~(-1),其中,叶占61.2%,果、枝和花分别占23.7%、10.5%和4.6%.②凋落叶总氮(TN)含量8月显著高于其他月份(p0.05),而TP含量在1—3月显著高于其他月份;C/N在8月显著低于其他月份(p0.05),而C/P及N/P在9月显著升高(p0.05).③在凋落叶分解过程中,C、N、P含量及其化学计量比随时间存在明显差异(p0.01),并且地上组TC、TN、C/N和C/P明显不同于地下组(p0.05).④在分解过程中,4种水解酶随时间存在明显差异(p0.01).⑤凋落叶酸性磷酸酶活性与土壤温度、电导率和凋落叶TP含量存在显著相关关系(p0.01).这些结果说明,秋茄凋落物产量及元素含量随季节变化存在明显差异;沉积作用对凋落叶分解过程中元素含量有显著影响,水解酶活性主要受凋落叶元素含量和土壤环境因子的控制.     

基于多源遥感数据的锡尔河中下游农田土壤水分反演

机器学习结合多源遥感数据反演土壤水分含量（SMC）是目前SMC研究的热点,因较少考虑温度、蒸散等重要SMC影响因子,反演结果存在一定的不确定性。利用Sentinel-1影像、MODIS产品和SRTM数据,提取雷达后向散射系数等32个SMC影响因子,经相关分析选择27个显著的SMC影响因子（P<0.05）作为反演因子,并设计三组因子组合。这三组因子组合分别与随机森林、支持向量回归、BP神经网络三种机器学习方法结合,发现基于随机森林结合所有因子的方案,其SMC反演精度最高,该组合均方根误差RMSE为0.039 m³/m³,将该方案被用于反演2017年生长季锡尔河流域中下游平原区农田SMC。结果表明：从上部至下部SMC总体呈逐渐增加的态势,但存在显著时空差异,春季和秋季SMC较高而夏季较低。SMC差异主要由土壤质地、热量条件和地表植被状况差异引起。春季平原区下部农田SMC要高于上部,SMC的主控因子是土壤质地和地表植被状况;在夏季,土壤水分的主控因子是热量条件,农田灌溉弥补了热量条件差异对土壤水分的影响,导致空间上平原上部和下部土壤SMC空间差异不显著;秋季SMC的主控因子植被状况抵消地表温度和土壤质地差异对SMC的影响,使得秋季SMC空间差异不显著。本文采用的研究方法在一定程度上克服了因考虑SMC影响因子不足而获取更高SMC精度的限制。     

SNOW: NATURE'S RESERVOIR1

ABSTRACT: Snow, one of Nature's greatest reservoirs, supplies most of the usable water in the Western United States. Reliable predictions of the quantity and timing of the release of this water are used in making management decisions involving irrigation, stock water and municipal water supplies, hydro-power generation, recreation, navigation, and pollution control Practically oriented research is vital for the proper development and management of this resource. In southwestern Idaho, the Northwest Watershed Research Center, ARS, USDA, is conducting intensive investigations for assessing snow Volumes, snow water content, and snow-melt over a watershed. Application of these research findings will result in better development and management of the water stored as snow in Nature's reservoir.