Mineralization,metabolism and formation of non-extractable residues of 14C-labelled organic contaminants during pilot-scale composting of municipal biowaste

Use of municipal biowaste for composting instead of its disposal has become a major source of concern as regards contamination by hazardous substances. To elucidate the hazard potential of compost application, municipal biowaste was amended with 14C-labelled model substances (pyrene, simazine) and incubated in a pilot-scale composting simulation system. A mass balance incorporating the mineralization, metabolism and sorption of the two model substances was established over a period of 370 days. The results are quite different for the two chemicals, reflecting their intrinsic properties: more than 60% of the applied 14C-simazine resulted in non-extractable residues (NER). Silylation experiments indicated that the formation of NER from simazine and its metabolites was due to both physical entrapment in the matrix and chemical binding. The mineralization and formation of NER represented the major pathways of disappearance for pyrene during one year of composting, accounting for 60 and 26% of initially applied 14C-activity, respectively. Mineralization occurred delayed after the thermophilic phase. As regards remobilization, release of pyrene from NER during composting could be excluded, whereas simazine, data were inconclusive in this respect.     

Concentration of LAS and boron in the Itter. Comparison of measured data with results obtained by simulation with the GREAT-ER software

The GREAT-ER software was used to calculate linear alkylbenzene sulphonate [LAS] and boron concentrations in the Itter stream in North Rhine-Westfalia, Germany. The aim was to investigate the predictive strength of this newly developed tool and to compare its results to measured data. Substance-specific input data which were used in this scenario were partly generic (e.g. LAS and sodium perborate tetrahydrate consumption figures for Germany) and partly (site-)specific data (e.g. half-life time for LAS elimination). The comparison with the measured data reveals that the model predictions for LAS and boron are correct at least within a factor of two, only if generic German consumption data is applied. By using refined input data, the accuracy can be increased further.     

Chapter three: methodology of exposure modeling

In this chapter, the concept of exposure assessment and its evolution is introduced, and evaluated by critically appraising the pertinent literature as it applies to exposures to Particulate Matter (PM). Exposure measurement or estimation methodologies and models are reviewed. Three exposure/measurement methodologies are assessed. Estimation methods focus on source evaluation and attribution, sources include those outdoors and indoors as well as in occupational and in-transit environments. Fate and transport models and their inputs are addressed to estimate concentrations outdoors and indoors; source attribution techniques help focus on the contributing sources. Activity pattern techniques are also reviewed and their use in exposure models to estimate inhalation exposure to PM is presented. Deterministic, regression and other stochastic models of exposure to PM are reviewed and evaluated. Strengths, limitations, assumptions and affirmations of the use of exposure assessment as an integral component of risk assessment and risk management are discussed in the conclusions and discussions section of this work.