Two New Polish Geological-Environmental Reference Materials: Apatite Concentrate (CTA-AC-1) and Fine Fly Ash (CTA-FFA-1)

World-wide intercomparison runs has made possible the certification of two new Polish geological-environmental reference materials for multi-element trace analysis: Apatite Concentrate (CTA-AC-1) and Fine Fly Ash (CTA-FFA-1). "Recommended values' are established for 25 (CTA-AC-1) and 40 (CTA-FFA-1) elements respectively. In addition, "information values' are assigned for 12 elements in CTA-AC-1 and 10 elements in CTA-FFA-1. Our method of data evaluation has been further improved and a modified version of criteria for assigning recommended and information values is proposed.     

Non-stationary random vibrations of a shear beam under high frequency seismic effects

Band-limited, non-stationary random vibrations of a shear beam are studied in order to investigate high frequency seismic effects on building structures. A solution for the evolutionary spectral density of the shear beam response to a time segment of band-limited white noise is given in a closed form. The root mean square (rms) and peak response of the shear beam are studied for two characteristic frequency bands: the conventional 1–4 Hz and higher frequency 4–16 Hz, characteristic for rockburst ground motion. Applying the criterion of equal excitation intensity with constant rms velocity, both responses are analyzed in detail and compared. The “switching off” fundamental mode for high frequency excitations results in characteristic overshoot of the stationary response level by the non-stationary rms response and an amplification of the response in the upper part of the shear beam.     

An Evaluation Of Local Similarity At The Top Of The Mixed Layer Based On Large-Eddy Simulations

Local similarity, referred to as type II similarity,in the interfacial, stably-stratified layer at thetop of the atmospheric (or oceanic) mixed layer isdiscussed. Type II scales for scalars are based onthe local values of scalar gradients. Similaritypredictions are derived from the second-orderclosure model of Yamada and Mellor, and also fromsimilarity arguments. The obtainedformulation is verified for active and passive scalarsbased on the large-eddy simulation model.     

Statistics of Scalar Fields in the Atmospheric Boundary Layer Based on Large-Eddy Simulations. Part II: Forced Convection

Forced convection in a quasi-steady atmospheric boundary layer is investigated based on a large-eddy simulation (LES) model. The performed simulations show that in the upper portion of the mixed layer the dimensionless (in terms of mixed layer scales) vertical gradients of temperature, humidity, and wind velocity depend on the dimensionless height z/z _i and the Reech number Rn. The peak values of variances and covariances at the top of the mixed layer, scaled in terms of the interfacial scales, are functions of the interfacial Richardson number Ri. As a result expressions for the entrainment rates, in the case when the interfacial layer has a finite depth, and a condition for the presence of moistening or drying regimes in the mixed layer, are derived. Profiles of dimensionless scalar moments in the mixed layer are proposed to be expressed in terms of two empirical similarity functions F _m and F _i , dependent on dimensionless height z/z _i , and the interfacial Richardson number Ri. The obtained similarity expressions adequately approximate the LES profiles of scalar statistics, and properly represent the impact of stability, shear, and entrainment. They are also consistent with the parameterization proposed for free convection in the first part of this paper.     

Improving resolution of a spatial air pollution inventory with a statistical inference approach

This paper presents a novel approach to allocation of spatially correlated data, such as emission inventories, to finer spatial scales, conditional on covariate information observable in a fine grid. Spatial dependence is modelled with the conditional autoregressive structure introduced into a linear model as a random effect. The maximum likelihood approach to inference is employed, and the optimal predictors are developed to assess missing values in a fine grid. An example of ammonia emission inventory is used to illustrate the potential usefulness of the proposed technique. The results indicate that inclusion of a spatial dependence structure can compensate for less adequate covariate information. For the considered ammonia inventory, the fourfold allocation benefited greatly from incorporation of the spatial component, while for the ninefold allocation this advantage was limited, but still evident. In addition, the proposed method allows correction of the prediction bias encountered for the upper range emissions in the linear regression models.     

Compliance for uncertain inventories via probabilistic/fuzzy comparison of alternatives

A direct comparison among highly uncertain inventories of emissions is inadequate and may lead to paradoxes. This issue is of particular importance in the case of greenhouse gases. This paper reviews the methods for the comparison of uncertain inventories in the context of compliance checking. The problem is treated as a comparison of uncertain alternatives. It provides a categorization and ranking of the inventories which can induce compliance checking conditions. Two groups of techniques to compare uncertain estimates are considered in the paper: probabilistic and fuzzy approaches. They show certain similarities which are revealed and stressed throughout the paper. The group of methods most suitable for the compliance purpose is distinguished. They introduce new conditions for fulfilling compliance, depending on inventory uncertainty. These new conditions considerably change the present approach, where only the reported values of inventories are accounted for.     

Simulation of an uncertain emission market for greenhouse gases using agent-based methods

The paper presents the problem of a simulation of the greenhouse gases emission permits market where only low accuracy emission amounts are known. An organization of the market with uncertain emissions is proposed and trading rules for individual market participants are discussed. Simulation of the market is based on a multi-agent system. Negotiation of purchase/sale prices between the parties are introduced, where the trading parties adopt one of two options: (i) bilateral negotiations, and (ii) sealed bid reverse auctions. Results of simulation runs show trajectories of transaction prices, as well as probability distributions of learning agents’ bidding prices.