Bioavailability aspects of hydrophobic contaminant degradation in soils

This thesis concentrates on bioavailability of organic soil contaminants in the context of bioremediation of soil contaminated with volatile or non-volatile hydrophobic pollutants. Bioavailability and biodegradation was studied from four viewpoints: (i) Improvement of bioavailability and biodegradation of volatile hydrocarbons in contained bioremediation systems at laboratory - and pilot-scale. (ii) Improvement of bioavailability of non-volatile, hydrophobic compounds in such systems. (iii) Biodegradation of a non-volatile hydrophobic compound in soil organic matter in microcosms. (iiii) Bioavailability of nitrogen in an open, full-scale bioremediation system. It was demonstrated that volatility of organic compounds can be controlled by amending the soil with adsorbents. The sorbed hydrocarbons were shown to be available to soil microbiota. As the result, biodegradation of the volatile hydrocarbons was greatly favored at the expense of volatilization. PAH compounds were shown to be mobilized and their bioavailability improved by a hydrophobic, non-toxic additive, vegetable oil. Bioavailability of the PAHs was recorded as an increased toxicity of the soil. In spite of the increased bioavailability, biodegradation of the PAHs decreased. In microcosms simulating boreal forest organic surface soil, PAH-compound (pyrene) was shown to be removed from soil biologically. Therefore hydrophobicity of the substrate does not necessarily mean low availability and biodegradation in organic soil. Finally, in this thesis it was demonstrated that an unsuitable source of nitrogen or its overdose resulted in wasteful spending of this nutrient and even harmful effects on soil microbes. Such events may inhibit rather than promote the bioremediation process in soil.

Methods and applications for improving parameter prediction models for stand structures in Finland

This thesis report attempts to improve the models for predicting forest stand structure for practical use, e.g. forest management planning (FMP) purposes in Finland. Comparisons were made between Weibull and Johnson s SB distribution and alternative regression estimation methods. Data used for preliminary studies was local but the final models were based on representative data. Models were validated mainly in terms of bias and RMSE in the main stand characteristics (e.g. volume) using independent data. The bivariate SBB distribution model was used to mimic realistic variations in tree dimensions by including within-diameter-class height variation. Using the traditional method, diameter distribution with the expected height resulted in reduced height variation, whereas the alternative bivariate method utilized the error-term of the height model. The lack of models for FMP was covered to some extent by the models for peatland and juvenile stands. The validation of these models showed that the more sophisticated regression estimation methods provided slightly improved accuracy. A flexible prediction and application for stand structure consisted of seemingly unrelated regression models for eight stand characteristics, the parameters of three optional distributions and Näslund s height curve. The cross-model covariance structure was used for linear prediction application, in which the expected values of the models were calibrated with the known stand characteristics. This provided a framework to validate the optional distributions and the optional set of stand characteristics. Height distribution is recommended for the earliest state of stands because of its continuous feature. From the mean height of about 4 m, Weibull dbh-frequency distribution is recommended in young stands if the input variables consist of arithmetic stand characteristics. In advanced stands, basal area-dbh distribution models are recommended. Näslund s height curve proved useful. Some efficient transformations of stand characteristics are introduced, e.g. the shape index, which combined the basal area, the stem number and the median diameter. Shape index enabled SB model for peatland stands to detect large variation in stand densities. This model also demonstrated reasonable behaviour for stands in mineral soils.