Determination of ground-water tracer 2,6-difluorobenzoic acid by Gc/Ms

In this study, a GC analytical method for the determination of the ground water tracer, 2,6-difluorobenzoic acid (2,6-DFBA) at the part per billion level was established. Three sample preparation methods, which include two methylation methods and one silylation method, have been evaluated. Chromatographic instruments including GC/MS, GC/ECD, and GC/FID have been used. Silylation of 2,6-DFBA combined with GC/MS analysis has proven to be the best method in this study, due to the low detection limits (part per trillion) achieved, and the stability of the 2,6-DFBA silyl derivative. A GC/MS instrument calibration curve was established, a C-well water sample was analyzed with this method and results were compared with HPLC analysis which has been used to analyze 2,6-DFBA at the part per billion level in ongoing studies; Since the GC/MS has the ability to separate the silyl derivatives of the various difluorobenzoate isomers, several difluorobenzoates can be analyzed simultaneously by this method in cases where multiple tracers are needed. More work should be done towards achieving better extraction efficiency and reducing the sample preparation time

Impacts of natural factors and farming practices on greenhouse gas emissions in the North China Plain : A meta-analysis

This work received support from the National Science and Technology Support Program (No. 2012BAD14B01), the National 948 Project (No. 2011-G30), and the Non-profit Research Foundation for Agriculture (201103039). Thanks are expressed to the anonymous reviewers for their helpful comments and suggestions that greatly improved the manuscript. The authors declare that they have no competing interests.Peer reviewedPublisher PD

Validating Sample Average Approximation Solutions with Negatively Dependent Batches

Sample-average approximations (SAA) are a practical means of finding approximate solutions of stochastic programming problems involving an extremely large (or infinite) number of scenarios. SAA can also be used to find estimates of a lower bound on the optimal objective value of the true problem which, when coupled with an upper bound, provides confidence intervals for the true optimal objective value and valuable information about the quality of the approximate solutions. Specifically, the lower bound can be estimated by solving multiple SAA problems (each obtained using a particular sampling method) and averaging the obtained objective values. State-of-the-art methods for lower-bound estimation generate batches of scenarios for the SAA problems independently. In this paper, we describe sampling methods that produce negatively dependent batches, thus reducing the variance of the sample-averaged lower bound estimator and increasing its usefulness in defining a confidence interval for the optimal objective value. We provide conditions under which the new sampling methods can reduce the variance of the lower bound estimator, and present computational results to verify that our scheme can reduce the variance significantly, by comparison with the traditional Latin hypercube approach

Mathematical Study and Numerical Simulation of Multispectral Bioluminescence Tomography

Multispectral bioluminescence tomography (BLT) attracts increasingly more attention in the area of optical molecular imaging. In this paper, we analyze the properties of the solutions to the regularized and discretized multispectral BLT problems. First, we show the solution existence, uniqueness, and its continuous dependence on the data. Then, we introduce stable numerical schemes and derive error estimates for numerical solutions. We report some numerical results to illustrate the performance of the numerical methods on the quality of multispectral BLT reconstruction