Comparison between UV spectroscopy and Nirs to assess humification process during sewage sludge and green wastes co-composting.

The humification of organic matter during composting was studied by the quantification and monitoring of the evolution of humic substances (Humic Acid-HA and Fulvic Acid-FA) by UV spectra deconvolution (UVSD) and near-infrared reflectance spectroscopy (NIRS) methods. The final aim of this work was to compare UVSD to NIRS method, already applied on the same compost samples in previous studies. Finally, UVSD predictions were good for HA and HA/FA (r(2) of 0.828 and 0.531) but very bad for FA (r(2) of 0.092). In contrary, all NIRS correlations were accurate and significant with r(2) of 0.817, 0.806 and 0.864 for HA, FA and HA/FA ratio respectively. From these results, HA/FA ratio being a well-used index of compost maturity, UVSD and NIRS represent two invaluable tools for the monitoring of the composting process. However, we can note that NIRS predictions were more accurate than UVSD calibrations.

Functional changes in culturable microbial communities during a co-composting process: carbon source utilization and co-metabolism.

Microbial communities in sewage sludge and green waste co-composting were investigated using culture-dependent methods and community level physiological profiles (CLPP) with Biolog Microplate. Different microbial groups characterized each stage of composting. Bacterial densities were high from beginning to end of composting, whereas actinomycete densities increased only after bio-oxidation phase i.e. after 40days. Fungal populations become particularly high during the last stage of decomposition. Cluster analyses of metabolic profiles revealed a similar separation between two groups of composts at 67days for bacteria and fungi. Principal component analysis (PCA) applied to bacterial and fungal CLPP data showed a chronological distribution of composts with two phases. The first one (before 67days), where the composts were characterized by the rapid decomposition of non-humic biodegradable organic matter, was significantly correlated to the decrease of C, C/N, organic matter (OM), fulvic acid (FA), respiration, cellulase, protease, phenoloxidase, alkaline and acid phosphatases activities. The second phase corresponding to the formation of polycondensed humic-like substances was significantly correlated to humic acid (HA) content, pH and HA/FA. The influent substrates selected on both factorial maps showed that microbial communities could adapt their metabolic capacities to the particular environment. The first phase seems to be focused on easily degradable substrate utilization whereas the maturation phase appears as multiple metabolisms, which induce the release of metabolites and their polymerization leading to humification processes.

Changes in the level of alkaline and acid phosphatase activities during green wastes and sewage sludge co-composting.

The aim of this work was to study the activity level of alkaline and acid phosphatases during the composting of green wastes and sewage sludge and to determine relationships between biotic and abiotic properties of compost and phosphatase activities. This study has revealed a noticeable separation of phosphomonoesterase activities into two distinct phases during composting. Alkaline and acid phosphatase activities were high during the first month of composting and then declined up to the end of the process. Both phosphatase activities were significantly correlated with a group of variables which are clearly related to advancement of maturity during the composting process: C/N, respiration, cellulase, protease, phenoloxidase activities, HA and Global Index of Composting Evolution (GICE) resulting from 14 biological and chemical parameters. This study has also revealed the complexity of factors regulating turnover of P in compost process since phosphatase activities appeared constrained across two thresholds: 60/70 and 100 microg of inorganic P g(-1) DM for activation and repression, respectively.

Calibration of chemical and biological changes in cocomposting of biowastes using near-infrared spectroscopy.

Cocomposting of green wastes and sewage sludges is a complex process involving rapid biological and chemical changes. The objective of the study was to assess the usefulness of near-infrared reflectance spectroscopy (NIRS) to characterize these changes, as an alternative to standard procedures which are often time-consuming and laborious. Samples obtained during 146 days of composting were analyzed by 14 conventional methods and NIRS. Results from conventional methods demonstrated a noticeable separation into two distinct phases. An initial phase from 4 to 50-60 days was characterized by intensive degradation. A second phase up to 146 days was characterized by a decrease in all biological activities. NIRS calibrations allowed accurate predictions of nitrogen (N), carbon (C), C/N, humic acid (HA), pH, respiration, cellulase, phenoloxidase, and composting time successfully. Results were less accurate for organic matter (OM), protease, acid, and alkaline phosphatases and unsatisfactory for fulvic acid. NIRS calibration allows composting time/state of progress of maturation to be predicted accurately to within 10 days. A global index of composting evolution (GICE), resulting from the 14 parameters studied, is proposed. It is precisely predicted and shows that since NIRS is able to predict essential parameters of compost maturity, it could prove invaluable for monitoring biowastes cocomposting.

Efficiency of near-infrared reflectance spectroscopy to assess and predict the stage of transformation of organic matter in the composting process.

Changes in composts of sewage sludges and green wastes were analysed by near infrared reflectance spectroscopy (NIRS) and chemical analysis with 426 samples representative of six stages of composting: 8, 20, 35, 75, 135 and 180 days. Maturity of compost was assessed through changes in C:N ratio. Results of spectroscopic properties (200 wavelengths) were studied with several multivariate analyses. First, a descriptive approach revealed compost changes with time of maturation. Then, a constrained ordination (RDA with permutation tests) demonstrated a significant effect of three factors of sampling: stage of composting, depth and position in windrows. Precise calibration models between spectral data, the C, N, C:N values and composting time were build using partial least square regression (r(2)>0.95). Together, these results show the efficiency of NIRS to predict chemical changes and the stage of transformation of organic matter during the composting process.