Impact of carbon/nitrogen feeding strategy on polyhydroxyalkanoates production using mixed microbial cultures

Polyhydroxyalkanoates (PHA) production using mixed microbial cultures (MMC) requires a multi-stage process involving the microbial selection of PHA-storing microorganisms, typically operated in sequencing batch reactors (SBR), and an accumulation reactor. Since low-cost renewable feedstocks used as process feedstock are often nitrogen-deficient, nutrient supply in the selection stage is required to allow for microbial growth. In this context, the possibility to uncouple nitrogen supply from carbon feeding within the SBR cycle has been investigated in this study. Moreover, three different COD:N ratios (100:3.79, 100:3.03 and 100:2.43) were tested in three different runs which also allowed the study of COD:N ratio on the SBR performance. For each run, a synthetic mixture of acetic and propionic acids at an overall organic load rate of 8.5 gCOD L-1 d-1 was used as carbon feedstock, whereas ammonium sulfate was the nitrogen source in a lab-scale sequence batch reactor (SBR) with 1 L of working volume. Besides, a sludge retention time (SRT) of 1 d was used as well as a 6 h cycle length. The uncoupled feeding strategy significantly enhanced the selective pressure towards PHA-storing microorganisms, resulting in a two-fold increase in the PHA production (up to about 1.3 gCOD L-1). A high storage response was observed for the two runs with the COD:N ratios (gCOD:gN) of 100:3.79 and 100:3.03, whereas the lowest investigated nitrogen load resulted in very poor performance in terms of polymer production. In fact, strong nitrogen limitation caused fungi to grow and a very poor storage ability by microorganisms that thrived in those conditions. The COD:N ratio also affected the polymer composition, indeed the produced poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) showed a variable HV content (1-20 %, w/w) among the three runs, lessening as the COD:N increased. This clearly suggests the possibility to use the COD:N ratio as a tool for tuning polymer properties regardless the composition of the feedstock.

Assessment of NDVI, land surface temperature and precipitation anomalies for drought monitoring in Bayankhongor province, Mongolia

During the last decade Mongolia’s region was characterized by a rapid increase of both severity and frequency of drought events, leading to pasture reduction. Drought monitoring and assessment plays an important role in the region’s early warning systems as a way to mitigate the negative impacts in social, economic and environmental sectors. Nowadays it is possible to access information related to the hydrologic cycle through remote sensing, which provides a continuous monitoring of variables over very large areas where the weather stations are sparse. The present thesis aimed to explore the possibility of using NDVI as a potential drought indicator by studying anomaly patterns and correlations with other two climate variables, LST and precipitation. The study covered the growing season (March to September) of a fifteen year period, between 2000 and 2014, for Bayankhongor province in southwest Mongolia. The datasets used were MODIS NDVI, LST and TRMM Precipitation, which processing and analysis was supported by QGIS software and Python programming language. Monthly anomaly correlations between NDVI-LST and NDVI-Precipitation were generated as well as temporal correlations for the growing season for known drought years (2001, 2002 and 2009). The results show that the three variables follow a seasonal pattern expected for a northern hemisphere region, with occurrence of the rainy season in the summer months. The values of both NDVI and precipitation are remarkably low while LST values are high, which is explained by the region’s climate and ecosystems. The NDVI average, generally, reached higher values with high precipitation values and low LST values. The year of 2001 was the driest year of the time-series, while 2003 was the wet year with healthier vegetation. Monthly correlations registered weak results with low significance, with exception of NDVI-LST and NDVI-Precipitation correlations for June, July and August of 2002. The temporal correlations for the growing season also revealed weak results. The overall relationship between the variables anomalies showed weak correlation results with low significance, which suggests that an accurate answer for predicting drought using the relation between NDVI, LST and Precipitation cannot be given. Additional research should take place in order to achieve more conclusive results. However the NDVI anomaly images show that NDVI is a suitable drought index for Bayankhongor province.