Kriging and Bilinear Methods for Estimating Spatial Pattern of Atmospheric Pollutants

Two statistical methods to reconstruct the spatial pattern ofenvironmental data are compared: the Kriging and the Bilinear.The comparison is performed by evaluating two differentcharacteristics of the methods: the interpolation and the estimation. The Kriging method is demonstrated to be better thanthe Bilinear regarding all the statistics studied, although thedifferences are not very significant. Especially, the Kriging ismore efficient than the Bilinear in the reconstruction of peakvalues and it does not extrapolate local trends. The methods areapplied to a set of environmental data measured in an urban area.     

基于单元分析的青铜峡灌区农业非点源污染估算

针对灌区农业非点源污染难以监测控制的具体特点,基于单元分析的观点,提出了负荷贡献率的概念,并在此基础上,建立了灌区农业非点源污染负荷估算方法;以青铜峡灌区为例,利用2005-2006年灌溉周期灌排水质监测试验资料对灌区年农业非点源污染矿化度、铵氮、总氮和总磷负荷进行了估算,并与平均浓度法进行比较.计算结果表明:青铜峡灌区农业非点源污染年输出盐分283万t,铵氮0.55万t,总氮4.11万t,总磷123 t;结合黄河干流控制断面水质资料比较分析,青铜峡灌区农业非点源污染负荷中盐分输出占干流区间增量的70%,铵氮和总氮分别是区间点源污染负荷的0.28倍和1.52倍,对黄河干流水质影响很大;而总磷由于输出量较小,对干流水质影响不大.     

Estimating an homogeneous series of a population abundance indicator despite changes in data collection procedure: A hierarchical Bayesian modelling approach

Abundance indicators are required both to assess and to manage wild populations. As new techniques are developed and teams in charge of gathering the data change, data collection procedures (DCPs) can evolve in space and time. How to estimate an homogeneous series of abundance indicator despite changes in DCP? To tackle this question a hierarchical Bayesian modelling (HBM) approach is proposed. It integrates multiple DCPs in order to derive a single abundance indicator that can be compared over space and time irrespective of the DCP used. Compared to single DCP models, it takes further advantage for abundance estimation of the joint treatment of a larger set of spatio-temporal units. After presenting the general formulation of our HBM approach, it is applied to the juvenile Atlantic salmon (Salmo salar L.) population of the River Nivelle (France). Posterior model checking, using χ² discrepancy measure, do not reveal any inadequacy between the model and the data. Despite a change in the DCP used (successive removals to catch-per-unit of effort), a unique abundance indicator for the 425 spatio-temporal units (site × year) sampled over twenty-four years (1985-2008) is estimated. The HBM approach allows the assessment of precision of the abundance estimates and shows variation between DCPs: a reduction in precision is observed during the most recent years (2005-2008) when only the catch-per-unit of effort DCP was used. The merits and generality of our HBM approach are discussed. We contend it extends previous single DCP models or inter-calibration of two DCPs, and it could be applied to a wide range of specific situations (taxon and DCPs).     

Estimating animal densities and home range in regions with irregular boundaries and holes: A lattice-based alternative to the kernel density estimator

Density estimates based on point processes are often restrained to regions with irregular boundaries or holes. We propose a density estimator, the lattice-based density estimator, which produces reasonable density estimates under these circumstances. The estimation process starts with overlaying the region with nodes, linking these together in a lattice and then computing the density of random walks of length k on the lattice. We use an approximation to the unbiased crossvalidation criterion to find the optimal walk length k. The technique is illustrated using walleye (Sander vitreus) radiotelemetry relocations in Lake Monroe, Indiana. We also use simulation to compare the technique to the traditional kernel density estimate in the situation where there are no significant boundary effects.     

天津市温室气体排放匡算

以2008年天津市主要领域碳排放情况为基数,采用IPCC指南中的计算方法,选取IPCC指南明确的五大领域中,对天津市而言具有代表性的部分内容,对2008年天津市全市碳排放量进行匡算.匡算结果表明,能源活动(化石燃料燃烧)为天津市主要温室气体排放源,且其比例占据了主导地位.在能源活动中工业和发电行业排放的温室气体较大,分...     

A Bayesian-weighted approach to predicting the number of newly discovered rare species

In natural ecological communities, most species are rare and thus susceptible to extinction. Consequently, the prediction and identification of rare species are of enormous value for conservation purposes. How many newly found species will be rare in the next field survey? We took a Bayesian viewpoint and used observed species abundance information in an ecological sample to develop an accurate way to estimate the number of new rare species (e.g., singletons, doubletons, and tripletons) in an additional unknown sample. A similar method has been developed for incidence-based data sets. Five seminumerical tests (3 abundance cases and 2 incidence cases) showed that our proposed Bayesian-weight estimator accurately predicted the number of new rare species with low relative bias and low relative root mean squared error and, accordingly, high accuracy. Finally, we applied the proposed estimator to 6 conservation-directed empirical data sets (3 abundance cases and 3 incidence cases) and found the prediction of new rare species was quite accurate; the 95% CI covered the true observed value very well in most cases. Our estimator performed similarly to or better than an unweighted estimator derived from Chao et al. and performed consistently better than the naïve unweighted estimator. We recommend our Bayesian-weight estimator for conservation applications, although the unweighted estimator of Chao et al. may be better under some circumstances. We provide an R package RSE (r are s pecies e stimation) at https://github.com/ecomol/RSE for implementation of the estimators.     

太湖水底摩擦系数的估算

利用１９９２年８月至１９９２年１０月在太湖马山地区测得的风，浪资料，采用浅水浪公式对太湖水底摩擦系数进行了估算，估算值为０．００２５。     

Modelling the biological performance of a side-stream membrane bioreactor using ASM1

Membrane bioreactors(MBRs) are attracting global interest but the mathematical modeling of the biological performance of MBRs remains very limited. This study focuses on the modelling of a side-stream MBR system using Activated Sludge Model No. 1 (ASM1), and comparing the results with the modelling of traditional activated sludge processes. ASM1 parameters relevant for the long-term biological behaviour in MBR systems were calibrated(i, e. YH = 0.72gCOD/gCOD, YA = 0.25gCOD/gN, bH = 0.25 d^-1, bA = 0.080 d^-1 and fp =0.06), and generally agreed with the parameters in traditional activated sludge processes, with the exception that a higher autotrophic biomass decay rate was observed in the MBR. A sensitivity analysis for steady state operation and DO dynamics suggested that the biological performance of the MBR system (the sludge concentration, effluent quality and the DO dynamics) are very sensitive to the parameters(i.e. YH, YA, bH, hA, μmaxH and μmaxA), and influent wastewater components( X1, Ss, Xs, SNH).     

Key emergency response technologies for abrupt air pollution accidents in China

Abrupt air pollution accidents can endanger people’s health and destroy the local ecological environment. The appropriate emergency response can minimize the harmful effects of accidents and protect people’s lives and property. This paper provides an overview of the key emergency response technologies for abrupt air pollution accidents around the globe with emphasis on the major achievements that China has obtained in recent years.With decades of effort, China has made significant progress in em...     

Evaluation of the International Vehicle Emission （IVE） model with on-road remote sensing measurements

Intemational Vehicle Emissions （IVE） model funded by U.S. Environmental Protection Agency （USEPA） is designed to estimate emissions from motor vehicles in developing countries. In this study, the IVE model was evaluated by utilizing a dataset available from the remote sensing measurements on a large number of vehicles at five different sites in Hangzhou, China, in 2004 and 2005. Average fuel-based emission factors derived from the remote sensing measurements were compared with corresponding emission factors derived from IVE calculations for urban, hot stabilized condition. The results show a good agreement between the two methods for gasoline passenger cars＇ HC emission for all 1VE subsectors and technology classes. In the case of CO emissions, the modeled results were reasonably good, although systematically underestimate the emissions by almost 12%-50% for different technology classes. However, the model totally overestimated NOx emissions. The IVE NOx emission factors were 1.5-3.5 times of the remote sensing measured ones. The IVE model was also evaluated for light duty gasoline truck, heavy duty gasoline vehicles and motor cycles. A notable result was observed that the decrease in emissions from technology class State II to State I were overestimated by the IVE model compared to remote sensing measurements for all the three pollutants. Finally, in order to improve emission estimation, the adjusted base emission factors from local studies are strongly recommended to be used in the IVE model.