Microbial biomass governs enzyme activity decay during aging of worm-worked substrates through vermicomposting

Vermicomposting is the biooxidation and stabilization of organic matter involving the joint action of earthworms and microorganisms, thereby turning wastes into a valuable soil amendment called vermicompost. Studies have focused on the changes in the type of substrates available before and after vermicomposting, but little is known on how these changes take place, especially those changes related with maturation of vermicompost. This study investigated the effects of aging on the microbiological properties of fresh vermicompost produced from pig slurry by analyzing the substrate after the earthworms had left it. We incubated 16-wk-old vermicompost and sampled it after 15, 30, 45, and 60 d analyzing microbial biomass and activity (assessed as microbial biomass N and basal respiration respectively) and four enzymatic activities (beta-glucosidase, cellulase, protease, and alkaline phosphatase). Aging of vermicompost resulted in decreases of microbial biomass and activity. Three of the four enzymes analyzed also showed decrease. An initial increase followed by a rapid decrease in alkaline phosphatase was also recorded. High and significant correlations between microbial biomass and beta-glucosidase (r = 0.62, P < 0.001), cellulase (r = 0.56, P < 0.01), and protease (r = 0.82, P < 0.001) were found. Results suggest that there may be two steps involved in the aging dynamics of vermicompost with regards to extracellular enzyme activity; the first step was characterized by a decrease in microbial populations, which resulted in a reduction in the synthesis of new enzymes. The second step was the degradation of the pool of remaining enzymes. This dynamic does not seem to be affected by earthworms because similar decaying patterns of microbial biomass and activity were found in substrate where earthworms were present.     

Costa Rica — Assessing Climate Mitigation Pathways to Support NDC Implementation

Environmental Modeling & Assessment - Costa Rica has set a very ambitious Nationally Determined Contribution (NDC). Despite the low-carbon footprint of its power sector, the goal set in its NDC...     

Microbiological characterization and specific methanogenic activity of anaerobe sludges used in urban solid waste treatment

This study presents the microbiological characterization of the anaerobic sludge used in a two-stage anaerobic reactor for the treatment of organic fraction of urban solid waste (OFUSW). This treatment is one alternative for reducing solid waste in landfills at the same time producing a biogas (CH(4) and CO(2)) and an effluent that can be used as biofertilizer. The system was inoculated with sludge from a wastewater treatment plant (WWTP) (Río Frío Plant in Bucaramanga-Colombia) and a methanogenic anaerobic digester for the treatment of pig manure (Mesa de los Santos in Santander). Bacterial populations were evaluated by counting groups related to oxygen sensitivity, while metabolic groups were determined by most probable number (MPN) technique. Specific methanogenic activity (SMA) for acetate, formate, methanol and ethanol substrates was also determined. In the acidogenic reactor (R1), volatile fatty acids (VFA) reached values of 25,000 mg L(-1) and a concentration of CO(2) of 90%. In this reactor, the fermentative population was predominant (10(5)-10(6)MPN mL(-1)). The acetogenic population was (10(5)MPN mL(-1)) and the sulphate-reducing population was (10(4)-10(5)MPN mL(-1)). In the methanogenic reactor (R2), levels of CH(4) (70%) were higher than CO(2) (25%), whereas the VFA values were lower than 4000 mg L(-1). Substrate competition between sulphate-reducing (10(4)-10(5)MPN mL(-1)) and methanogenic bacteria (10(5)MPN mL(-1)) was not detected. From the SMA results obtained, acetoclastic (2.39 g COD-CH(4)g(-1)VSS(-1)day(-1)) and hydrogenophilic (0.94 g COD-CH(4)g(-1)VSS(-1)day(-1)) transformations as possible metabolic pathways used by methanogenic bacteria is suggested from the SMA results obtained. Methanotrix sp., Methanosarcina sp., Methanoccocus sp. and Methanobacterium sp. were identified.     

Modeling and forecasting daily maximum hourly ozone concentrations using the RegAR model with skewed and heavy-tailed innovations

This paper considers the modeling and forecasting of daily maximum hourly ozone concentrations in Laranjeiras, Serra, Brazil, through dynamic regression models. In order to take into account the natural skewness and heavy-tailness of the data, a linear regression model with autoregressive errors and innovations following a member of the family of scale mixture of skew-normal distributions was considered. Pollutants and meteorological variables were considered as predictors, along with some deterministic factors, namely week-days and seasons. The Oceanic Niño Index was also considered as a predictor. The estimated model was able to explain satisfactorily well the correlation structure of the ozone time series. An out-of-sample forecast study was also performed. The skew-normal and skew-t models displayed quite competitive point forecasts compared to the similar model with gaussian innovations. On the other hand, in terms of forecast intervals, the skewed models presented much better performance with more accurate prediction intervals. These findings were empirically corroborated by a forecast Monte Carlo experiment.