Multicriteria prioritization and partial order in environmental sciences

The complexity of the present data-centric world finds its expression in the increasing number of multi-indicator systems. This has led to the development of multicriteria ranking systems based on partial orders. Order theory is a main pillar of structural mathematics. Partial orders help to reveal why an object of interest holds a certain ranking position and how much it is subject to change if a composite indicator is upgraded. Order theory helps to derive linear or weak orders without indicator weighting schemes. Hence, rankings obtained from decision support systems (DSS) which depend on many parameters beyond the data matrix can be checked and discrepancies can lead to examine the parameters of the DSS. Order theory helps discover association and implication structures derived from formal concept lattices. Association and implication networks among the attributes of the data matrix allow more insights into multi-indicator systems and lead to new hypotheses and motivate further research. Some new and innovative concepts, like separated subsets, antagonistic indicators, ranking stability fields are rendered. Separated subsets are the typical outcome of a partial order analysis; their identification leads to antagonistic indicators, which are responsible for the separatedness of object’s subsets. Numerical aggregation can be performed step-by-step and the question which values of a weight lead to an order inversion is of high interest. The concept of stability fields is one possible answer, discussed in this paper. After an outline of partial order theory some more specific theoretical results are shown, then we discuss the role of composite indicators in the light of partial order and give some examples of interesting applications of partial order. Finally examples are selected from real life case studies of watersheds, environmental performance evaluations, child well being, geographic and administrative regions and more.     

Metal-free oxidation of aldehydes to acids using the 4Na<Subscript>2</Subscript>SO<Subscript>4</Subscript>·2H<Subscript>2</Subscript>O<Subscript>2</Subscript>·NaCl adduct

Oxidation of aldehydes to carboxylic acids is a major reaction. Conventionally, this reaction is carried out with oxidants and metal catalysts, thus producing unwanted metal waste. Recently, aqueous media have been used as an alternative for toxic organic solvents. Here, we tested the clathrate-structured, neutral hydrogen peroxide adduct 4Na₂SO₄·2H₂O₂·NaCl for the oxidation of aldehydes to acids in aqueous solution. We found that various aromatic, heteroaromatic and aliphatic aldehydes were selectively oxidized to corresponding acids in 70–98% yields. This simple acid–base treatment allows to separate easily the acid product in high purity without any organic solvent. Moreover, the adduct is produced using 25% H₂O₂, with inexpensive sodium sulphate, Na₂SO₄, and sodium chloride, NaCl. The adduct is a non-toxic white crystalline solid, readily soluble in water, and easy to handle.     

Trisomy 12 mosaicism in phenotypically normal fetuses following prenatal detection

We report three cases of amniocentesis in which mosaicism for trisomy 12 was detected in two or more independent cultures. The parents elected to terminate the pregnancy in all three cases. Follow-up studies in two of the cases confirmed the mosaicism in fetal tissues (in subcutaneous tissue in one case; in fetal lung in the other), but not in blood. No fetal anomalies were evident by ultrasound or at autopsy. These results along with other reported cases demonstrate the difficulty in counselling for mosaic trisomy 12.     

Use of landscape and land use parameters for classification and characterization of watersheds in the mid-Atlantic across five physiographic provinces

The Atlantic Slope Consortium (ASC) is a project designed to develop and test a set of indicators in coastal systems that are ecologically appropriate, economically reasonable, and relevant to society. The suite of indicators will produce integrated assessments of the condition, health and sustainability of aquatic ecosystems based on ecological and socioeconomic information compiled at the scale of estuarine segments and small watersheds. The research mandate of the ASC project is the following:

Using a universe of watersheds, covering a range of social choices, we ask two questions:

• ? How “good” can the environment be, given those social choices?
• ? What is the intellectual model of condition within those choices, i.e., what are the causes of condition and what are the steps for improvement?

As a basis for compiling ecological indicators, a watershed classification system was required for the experimental design. The goal was to develop approximately five categories of watersheds for each physiographic province, utilizing landscape and land use parameters that would be predictive of aquatic resource condition. All 14-digit Hydrologic Unit Code (HUC) watersheds in the Mid-Atlantic region would then be classified according to the regime. Five parameters were utilized for the classification: three land cover categories, consisting of forested, agricultural, and urban, median slope or median elevation, and total variance of land covers in 1-km-radius circles positioned on all stream convergence points in a specified 14-digit?HUC watershed. Cluster analysis utilizing these five parameters resulted in approximately five well-defined watershed classes per physiographic province. The distribution of all watersheds in the Mid-Atlantic region across these categories provides a unique report on the probable condition of watersheds in the region.     

Identifying extremely large values using composite sample data

Quantifying a composite sample results in a loss of information on the values of the constituent individual samples. As a consequence of this information loss, it is impossible to identify individual samples having large values, based on composite sample measurements alone. However, under certain circumstances, it is possible to identify individual samples having large values without exhaustively measuring all individual samples. In addition to composite sample measurements, a few additional measurements on carefully selected individual samples are sufficient to identify the individual samples having large values. In this paper, we present a statistical method to recover extremely large individual sample values using composite sample measurements. An application to site characterization is used to illustrate the method.The paper has been prepared with partial support from the United States Environmental Protection Agency Number CR815273. The contents have not been subject to Agency review and therefore do not necessarily reflect the views or policies of the Agency and no official endorsement should be inferred.     

A Simple Model to Determine In Situ Mixing Height Growth from Surface Measurements

A generic In Situ Mixing Height Growth (IMG) model, capable of predicting the real-time growth of the mixed layer and its diurnal evolution from routinely observed simple surface meteorological is developed. The algorithm for the determination of temporally growing daytime mixing height includes both convective and mechanical turbulence contributions. It accounts for neutral as well as height varying potential temperature gradients above the mixed layer. For thermally stable and mechanically dominated unstable night time Atmospheric Boundary Layer (ABL) the module uses similarity formulae based on the wind velocity [1]), the Monin—Obukhov length [2], and the Coriolis parameter. In the convective case simple slab model is integrated, based on initial lapse rate and the surface heat flux. The lapse rate is evaluated on the basis of vertical atmospheric stability, surface type and surface temperature. This differentiates the IMG model from other existing mixing height models that need initial measured lapse rate for calculation. IMG model is site specific as it calculates the radiative incoming heat flux depending on the solar declination estimates based on-site latitude and longitude. The IMG model is applied to calculate mixing height for India by using surface data (viz. wind speed, surface temperature, surface type) from 152 surface meteorological stations. Results have been evaluated with radiosonde mixing height data procured from 18 upper air stations. Sensitivity analysis of the model with respect to various parameters is performed. The model is formulated after reviewing presently available radiosonde mixing height data in India and can satisfactorily provide an alternative means of estimating mixing height for air pollution dispersion models.     

Qualitative and quantitative assessment of the risk from the exposure to fetotoxic chemical compounds

A new mathematical dose-response model for the expected probability of toxic response and also for the expected measure of the overdispersion parameter for the reproductive and developmental risk assessment is proposed. The model for the expected probability of toxic response is an improvised Weibull dose-response model incorporating the litter-size effect while the model for the overdispersion parameter is a polynomial function of the dose level. A beta-binomial distribution for the number of offspring showing toxic responses in a litter satisfactorily accounts for the extra-binomial variation and the intralitter correlation of responses of these pups. Confidence limits for low-dose extrapolation are based on the asymptotic distribution of the likelihood ratio. The safe dose for human exposure is then calculated by simple linear extrapolation. The model for overdispersion allows us to obtain the estimates of the overdispersion parameter at these dosages. This was not possible in the earlier models. The proposed model is illustrated by an application to a study on the effect of exposure to diethylhexylphthalate in mice. The results are compared with those obtained by Chen and Kodell (1989) who have applied the simple Weibull dose-response model to the same data set.This paper was prepared with partial support from the United States Environmental Protection Agency under a Cooperative Agreement Number CR-815273. The contents have not been subject to Agency review and therefore do not necessarily reflect the views or policies of the Agency and no official endorsement should be inferred.