ICP-AES测定电镀污泥中的金和钯

介绍了含贵金属电镀污泥的样品采集、制备和预处理方法,并对有关问题进行了讨论.研究了电感耦合等离子体-原子发射光谱(ICP-AES)直接测定电镀污泥中微量金、钯的分析方法.结果表明:在选定的最佳仪器工作条件下,金、钯的检出限分别为0.015和0.018 mg/L,加标回收率为94.0%～104.0%,相对标准偏差小于3%.该方法可用于电镀污泥中微量金、钯的测定      

Comparison of sensitivity analysis techniques: A case study with the rice model WARM

The considerable complexity often included in biophysical models leads to the need of specifying a large number of parameters and inputs, which are available with various levels of uncertainty. Also, models may behave counter-intuitively, particularly when there are nonlinearities in multiple input-output relationships. Quantitative knowledge of the sensitivity of models to changes in their parameters is hence a prerequisite for operational use of models. This can be achieved using sensitivity analysis (SA) via methods which differ for specific characteristics, including computational resources required to perform the analysis. Running SA on biophysical models across several contexts requires flexible and computationally efficient SA approaches, which must be able to account also for possible interactions among parameters. A number of SA experiments were performed on a crop model for the simulation of rice growth (Water Accounting Rice Model, WARM) in Northern Italy. SAs were carried out using the Morris method, three regression-based methods (Latin hypercube sampling, random and Quasi-Random, LpTau), and two methods based on variance decomposition: Extended Fourier Amplitude Sensitivity Test (E-FAST) and Sobol’, with the latter adopted as benchmark. Aboveground biomass at physiological maturity was selected as reference output to facilitate the comparison of alternative SA methods. Rankings of crop parameters (from the most to the least relevant) were generated according to sensitivity experiments using different SA methods and alternate parameterizations for each method, and calculating the top-down coefficient of concordance (TDCC) as measure of agreement between rankings. With few exceptions, significant TDCC values were obtained both for different parameterizations within each method and for the comparison of each method to the Sobol’ one. The substantial stability observed in the rankings seem to indicate that, for a crop model of average complexity such as WARM, resource intensive SA methods could not be needed to identify most relevant parameters. In fact, the simplest among the SA methods used (i.e., Morris method) produced results comparable to those obtained by methods more computationally expensive.     

Detecting Rare Species with Random or Subjective Sampling: a Case Study of Red-Listed Saproxylic Beetles in Boreal Sweden

Abstract:  Efficient sampling design in field studies is important for economical and statistical reasons. We compared two ways to distribute sampling effort over an area, either randomly or subjectively. We searched for red-listed saproxylic (wood-living) beetles in 30 spruce stands in boreal Sweden by sifting wood from dead trees. We randomly selected positions within each stand with a geographic positioning system and sampled the nearest dead tree (random sample). In the same stand we also sampled dead trees that, based on literature, were likely to host such species (subjective sampling). The subjective sampling (two to five samples per stand, depending on stand size) was compared with the higher, random sampling effort (fixed level of 12 samples/stand). Subjective sampling was significantly more efficient. Red-listed species were found in 36% of the subjective samples and in 16% of the random samples. Nevertheless, the larger random effort resulted in a comparable number of red-listed species per stand and in 13 detected species in total (vs. 12 species with subjective sampling). Random sampling was less efficient, but provided an unbiased alternative more suitable for statistical purposes, as needed in, for example, monitoring programs. Moreover, new species-specific knowledge can be gained through random searches.     

Isochromosome 5p mosaicism at prenatal diagnosis: observations and outcomes in six cases at chorionic villus sampling and one at amniocentesis

We present six cases of 47,+i(5p)/46 mosaicism diagnosed at chorionic villus sampling (CVS), this being the first prospective series to be reported. The clinical indication in each was advanced maternal age. Further prenatal studies in four (amniocentesis, plus fetal blood sampling in one) did not show the isochromosome. In one case, subsequent amniocentesis showed 1/48 in situ colonies with the isochromosome, but fetal blood was karyotypically normal. These five pregnancies resulted in phenotypically normal livebirths; further normal follow-up reports (from age 4 months through 4 years) are noted in four of these. Analysis of placental tissue in one case confirmed the presence of the i(5p) mosaicism. In the remaining case, in which 100% of CVS cultured cells had the i(5p), the pregnancy was terminated. Fetal skin fibroblasts did not show the i(5p). Thus, in none of these six cases was true fetal mosaicism detected, nor an abnormal phenotype noted. We suggest that a 47,+i(5p)/46 karyotype, detected at CVS, may frequently reflect confined placental mosaicism. In addition, we report a case of the primary diagnosis of 47,+i(5p)/46 mosaicism at amniocentesis. The infant appeared normal at birth, but a brain malformation was subsequently identified. Copyright © 2002 John Wiley & Sons, Ltd.     

Prenatal diagnosis of infantile hypophosphatasia

Prenatal diagnosis was attempted in a pregnant Japanese woman whose son had died of infantile hypophosphatasia, using chorionic villi sampled at 10 weeks of gestation. Southern blot analysis of restriction fragment length polymorphism was used as a guide, with cDNA for the human liver-type alkaline phosphatase as a probe, and BclI as a restriction enzyme. The fetus was found to be a heterozygote; the pregnancy was allowed to continue; and the baby born was phenotypically normal.     

Optimizing Liquid Effluent Monitoring at a Large Nuclear Complex

Effluent monitoring typically requires a large number of analytes and samples during the initial or startup phase of a facility. Once a baseline is established, the analyte list and sampling frequency may be reduced. Although there is a large body of literature relevant to the initial design, few, if any, published papers exist on updating established effluent monitoring programs. This paper statistically evaluates four years of baseline data to optimize the liquid effluent monitoring efficiency of a centralized waste treatment and disposal facility at a large defense nuclear complex. Specific objectives were to: (1) assess temporal variability in analyte concentrations, (2) determine operational factors contributing to waste stream variability, (3) assess the probability of exceeding permit limits, and (4) streamline the sampling and analysis regime. Results indicated that the probability of exceeding permit limits was one in a million under normal facility operating conditions, sampling frequency could be reduced, and several analytes could be eliminated. Furthermore, indicators such as gross alpha and gross beta measurements could be used in lieu of more expensive specific isotopic analyses (radium, cesium-137, and strontium-90) for routine monitoring. Study results were used by the state regulatory agency to modify monitoring requirements for a new discharge permit, resulting in an annual cost savings of US $223,000. This case study demonstrates that statistical evaluation of effluent contaminant variability coupled with process knowledge can help plant managers and regulators streamline analyte lists and sampling frequencies based on detection history and environmental risk.     

A STAGE-ACTIVATED TRIGGERING DEVICE FOR AUTOMATIC PUMPING SAMPLERS1

A device to trigger automatic pumping samplers at discrete stages on headwater streams in southeastern Oklahoma was developed. The magnetic switch column employs a sequence of magnetic reed switches wired in parallel and set at 0.03 m (0.10 ft) intervals. A magnetic float inside the column closes the reed switches, therby triggering the sampler as stage rises and falls. The columns were constructed from inexpensive, readily-available materials. Following installation and field calibration, the columns provided relaible and representative sampling during 12 storms, at three sites. The magnetic switch column may be used in a wide range of research and monitoring sites to improve water quality sampling.     

Comparison of maternal and fetal chromosome heteromorphisms to monitor maternal cell contamination in chorionic villus samples

Maternal cell contamination (MCC) presents a potential problem in the analysis of chorionic villus sampling (CVS) preparations for early prenatal diagnosis by chromosomal, biochemical and molecular methods. Through the comparison of fluorescent chromosome variants from CVS and maternal cells, we found three out of 50 samples to have MCC. One of these was observed on a direct preparation. Routine chromosome heteromorphism analysis suggested as a reliable method for monitoring MCC in CVS specimens.     

ASSESSMENT OF SAMPLING ERROR ASSOCIATED WITH SOIL MOISTURE ESTIMATION DESIGNS1

A spectral formalism was developed and applied to quantify the sampling errors due to spatial and/or temporal gaps in soil moisture measurements. A design filter was developed to compute the sampling errors for discrete measurements in space and time. This filter has as its advantage a general form applicable to various types of sampling design. The lack of temporal measurements of the two‐dimensional soil moisture field made it difficult to compute the spectra directly from observed records. Therefore, the wave number frequency spectra of soil moisture data derived from stochastic models of rainfall and soil moisture were used. Parameters for both models were estimated using data from the Southern Great Plains Hydrology Experiment (SGP97) and the Oklahoma Mesonet. The estimated sampling error of the spatial average soil moisture measurement by airborne L‐band microwave remote sensing during the SGP97 hydrology experiment is estimated to be 2.4 percent. Under the same climate conditions and soil properties as the SGP97 experiment, equally spaced ground probe networks at intervals of 25 and 50 km are expected to have about 16 percent and 27 percent sampling error, respectively. Satellite designs with temporal gaps of two and three days are expected to have about 6 percent and 9 percent sampling errors, respectively.