Monitoring microbial community in a subsurface soil contaminated with hydrocarbons by quinone profile

A natural attenuation experiment was carried out using a lysimeter for 308 days after contaminating the subsoil with hydrocarbons (HCs) and the changes in the structures of microbial community in the hydrocarbon (HC) contaminated subsoil were monitored by quinone profile analysis. The residues of HCs remained for 217 days in the subsoil after the contamination. The amount of total quinones (TQ), an indicator of microbial biomass, significantly increased in the HC contaminated subsoil for 217 days, comparing with that of the background subsoil or the subsoil before the addition of HCs. The major quinone species and the quinone composition, indicators of community structure, were significantly different between the HC contaminated soil and the background soil for 217 days. The major increased quinine species in the HC contaminated soil were menaquinone-8(H4), menaquinone-9(H2) and ubiquinone-9, indicating the propagation of Gram-positive bacteria with high guanine and cytosine content and gamma-subclass of Proteobacteria and fungi. There was no significant difference in the diversity of the quinone species (DQ), an indicator of taxonomic diversity of microbial community, except for the decrease in DQ in the shallow subsoil after 35 days when a high concentration of HCs was detected. After 308 days when the HCs in the subsoil disappeared, TQ returned to the level of the background soil, and no significant difference in quinone composition were observed between the HC contaminated soil and the background soil. The results suggested that respiratory quinones are effective biomarkers for characterizing the temporal changes of microbial community in the HC contaminated subsoil.     

The chemical characteristics of ashes from cattle, swine and poultry manure

Animal manure is waste that contains large amounts of fertilizer resources. Incineration technology is effective in decreasing the volume of animal manure and concentrating the nutrients. In this study, the nutrient concentration and chemical compounds of several types of animal manure ash were examined to promote their recycling for agriculture. The nutrient concentration of manure ash was dependent on the reduction rate of solid materials by incineration. The phosphorus (P) and potassium (K) of cattle and layer manure were not concentrated greatly because of high silicon (Si) and calcium (Ca) concentrations, respectively. On the other hand, the P concentration of swine manure and broiler litter was increased to 10.1–12.0 % (3.6–4.6 times compared with original materials), equivalent to that of phosphate rock used as fertilizer material. The K concentration of broiler litter ash (16.1 %) was highest of all. The phosphate compounds of cattle and swine manure ashes were determined as Ca₉Fe(PO₄)₇ or Ca₉MgK(PO₄)₇. Hydroxyapatite (Ca₅(PO₄)₃(OH)) was detected in layer manure and broiler litter ashes. By acid treatment of ash, P and K availability of the fertilizer made from layer manure ash (33 % of materials) was equivalent to that of conventional chemical fertilizer.     

Tracer transport model at Japan meteorological agency and its application to the ETEX data

This paper describes the JMA tracer transport model and its sensitivity to model physics and initial conditions by using the ETEX data. Compared with observations, the model overestimates ground-level concentration in the early stage within about one day from the emission, possibly due to underestimation of vertical diffusion. In the early stage, the enhanced vertical diffusion effectively transports the tracer upward and decreases the ground-level concentration, while in the later stage, it enhances downward transports from the upper layer and increases the ground-level concentration. A conceptual model is given for understanding the vertical transport due to vertical diffusion. The horizontal diffusion introduced to the model has preferable impacts on forecasts especially in the early stage. Finally, we discuss the predictability of this model based on sensitivity to initial conditions of emission time and height.