深孔定点快速取样技术在瓦斯含量测定中的应用效果考察

煤层瓦斯含量是煤与瓦斯突出矿井区域措施效果检验的重要参数之一,而目前我国大多数突出矿井采掘工作面经预抽煤层瓦斯后进行瓦斯含量测定时,采用孔口接粉的方式采集煤样,往往导致采样时间不满足相关标准要求,测定结果的准确性和可靠程度偏低。基于此现状,开发研制了深孔定点快速取样装置,通过在河南某矿己15煤层24080回采工作面区域措施效果检验中的考察试验,与孔口接粉的取样方法进行了对比,考察结果表明,深孔定点快速取样时间小于5 min ,上向孔最大取样深度达93 m、下向孔最大取样深度达75 m ,实现了回采工作面大孔深快速取样,基于深孔定点快速取样的瓦斯含量测定结果的准确性和可靠性更高。     

《地下水管理条例》实施后的金属指标检测样品采集及前处理规范性分析

《地下水管理条例》自2021年12月1日起施行,但是由于《地下水质量标准》(GB/T 14848—2017)未明确其中的金属指标是检测可溶态含量还是总量,导致各检测机构在检测过程中的采样和前处理环节存在较多不确定之处。梳理了国内外地下水监测相关标准和规范,并进行了实验比对,经分析得出以下结论:铜、铅、锌、铁、锰的可溶态含量和总量检测结果存在明显差异,其中,铁和铅检测结果的差异最明显,铁和锰检测结果的差异会影响地下水质量类别判定。《地下水质量标准》中的金属指标应检测可溶态,包括汞、砷和硒。充分洗井后采集的地下水样品存在一定的浑浊度是合理的。完成采集的地下水金属指标检测样品中不应包含沉淀相。测定地下水可溶态汞、砷和硒时,如采用原子荧光法,则需对样品进行消解;如采用电感耦合等离子体质谱法,则无需对样品进行消解。在此基础上,对地下水采样及前处理关键环节和地下水检测管理工作提出了相关建议。     

气体污染源中总氟的监测方法研究

通过对玻璃纤维滤筒的预处理,在等速采样情况下达到完全捕捉烟气中的总氟。     

Long-Term Biomonitoring with Lichens: Comparing Data from Different Sampling Procedures

The results of 2 biomonitoring surveys carried out over a span of 7 years (1996–2003) in the Province of Ancona (central Italy) using the diversity of epiphytic lichens are reported. According to a recent standardisation process, in 2003 a different protocol was adopted, raising the problem of data comparability with the previous study. For this reason, a ‘pilot study' was carried out in which the two sampling tactics were both used. The high correlation between biodiversity values proved by the results of this study, let to compare the two lichen diversity data set and to identify the impacts on lichen communities of temporal variations of atmospheric quality in the study area, showing a reduction of stations classified as ‘altered' and an increase in stations classified as ‘semi-altered'. Furthermore, possible reduction of the sampling effort was detected performing a study on the sampling density of the survey area, indicating in a 6 × 6 km grid the best density to adopt in order to save financial resources for the future.     

Function Approximation and Documentation of Sampling Data Using Artificial Neural Networks

Biodiversity studies in ecology often begin with the fitting and documentation of sampling data. This study is conducted to make function approximation on sampling data and to document the sampling information using artificial neural network algorithms, based on the invertebrate data sampled in the irrigated rice field.Three types of sampling data, i.e., the curve species richness vs. the sample size, the curve rarefaction, and the curve mean abundance of newly sampled species vs.the sample size, are fitted and documented using BP (Backpropagation) network and RBF (Radial Basis Function) network. As the comparisons, The Arrhenius model, and rarefaction model, and power function are tested for their ability to fit these data. The results show that the BP network and RBF network fit the data better than these models with smaller errors.BP network and RBF network can fit non-linear functions (sampling data) with specified accuracy and don't require mathematical assumptions. In addition to the interpolation, BP network is used to extrapolate the functions and the asymptote of the sampling data can be drawn. BP network cost a longer time to train the network and the results are always less stable compared to the RBF network. RBF network require more neurons to fit functions and generally it may not be used to extrapolate the functions. The mathematical function for sampling data can be exactly fitted using artificial neural network algorithms by adjusting the desired accuracy and maximum iterations. The total numbers of functional species of invertebrates in the tropical irrigated rice field are extrapolated as 140 to 149 using trained BP network, which are similar to the observed richness.     

A Water Quality Monitoring Network Design Methodology for the Selection of Critical Sampling Points: Part I

The principal instrument to temporally and spatially manage water resources is a water quality monitoring network. However, to date in most cases, there is a clear absence of a concise strategy or methodology for designing monitoring networks, especially when deciding upon the placement of sampling stations. Since water quality monitoring networks can be quite costly, it is very important to properly design the monitoring network so that maximum information extraction can be accomplished, which in turn is vital when informing decision-makers. This paper presents the development of a methodology for identifying the critical sampling locations within a watershed. Hence, it embodies the spatial component in the design of a water quality monitoring network by designating the critical stream locations that should ideally be sampled. For illustration purposes, the methodology focuses on a single contaminant, namely total phosphorus, and is applicable to small, upland, predominantly agricultural-forested watersheds. It takes a number of hydrologic, topographic, soils, vegetative, and land use factors into account. In addition, it includes an economic as well as logistical component in order to approximate the number of sampling points required for a given budget and to only consider the logistically accessible stream reaches in the analysis, respectively. The methodology utilizes a geographic information system (GIS), hydrologic simulation model, and fuzzy logic.     

模式采样法采集尾气中BaP的研究

用模式了取样法集汽车柴油发动机尾气中多环茎烃,并重点对ＢａＰ采样方法进行研究,结果表明,该法采样时间仅１－２ｓ,采样体积为３３０ｍｌ（ｓ．次）,回收率７７．６％,９次重复的变异系数为２９．６％,测得ＢａＰ的数据与国际ＩＳＯ规定的ＣＶＳ定容取样法可比。     

罐采样-GC/MS测定空气中挥发性有机物方法

建立了罐(SUMMA)采样GC/MS测定空气中38种挥发性有机物的方法,详尽地叙述了采样及分析过程。方法检出限在0.01～0.03μg/m3。     

The potential effect of differential ambient and deployment chamber temperatures on PRC derived sampling rates with polyurethane foam (PUF) passive air samplers

Performance reference compound (PRC) derived sampling rates were determined for polyurethane foam (PUF) passive air samplers in both sub-tropical and temperate locations across Australia. These estimates were on average a factor of 2.7 times higher in summer than winter. The known effects of wind speed and temperature on mass transfer coefficients could not account for this observation. Sampling rates are often derived using ambient temperatures, not the actual temperatures within deployment chambers. If deployment chamber temperatures are in fact higher than ambient temperatures, estimated sampler-air partition coefficients would be greater than actual partition coefficients resulting in an overestimation of PRC derived sampling rates. Sampling rates determined under measured ambient temperatures and estimated deployment chamber temperatures in summer ranged from 7.1 to 10 m³ day⁻¹ and 2.2-6.8 m³ day⁻¹ respectively. These results suggest that potential differences between ambient and deployment chamber temperatures should be considered when deriving PRC-based sampling rates.     

Validation of regression models for nitrate concentrations in the upper groundwater in sandy soils

For Dutch sandy regions, linear regression models have been developed that predict nitrate concentrations in the upper groundwater on the basis of residual nitrate contents in the soil in autumn. The objective of our study was to validate these regression models for one particular sandy region dominated by dairy farming. No data from this area were used for calibrating the regression models. The model was validated by additional probability sampling. This sample was used to estimate errors in 1) the predicted areal fractions where the EU standard of 50 mg l⁻¹ is exceeded for farms with low N surpluses (ALT) and farms with higher N surpluses (REF); 2) predicted cumulative frequency distributions of nitrate concentration for both groups of farms.Both the errors in the predicted areal fractions as well as the errors in the predicted cumulative frequency distributions indicate that the regression models are invalid for the sandy soils of this study area.