Supercritical water gasification of RDF and its components over RuO2/γ-Al2O3 catalyst:new insights into RuO2 catalytic reaction mechanisms

Five samples including a composite refuse derived fuel (RDF) and four combustible components of municipal solid wastes (MSW) have been reacted under supercritical water conditions in a batch reactor. The reactions have been carried out at 450 °C for 60 min reaction time, with or without 20 wt% RuO2/gamma-alumina catalyst. The reactivities of the samples depended on their compositions; with the plastic-rich samples, RDF and mixed waste plastics (MWP), giving similar product yields and compositions, while the biogenic samples including mixed waste wood (MWW) and textile waste (TXT) also gave similar reaction products. The use of the heterogeneous ruthenium-based catalyst gave carbon gasification efficiencies (CGE) of up to 99 wt%, which was up by at least 83% compared to the non-catalytic tests. In the presence of RuO2 catalyst, methane, hydrogen and carbon dioxide became the dominant gas products for all five samples. The higher heating values (HHV) of the gas products increased at least two-fold in the presence of the catalyst compared to non-catalytic tests. Results show that the ruthenium-based catalyst was active in feedstock steam reforming, methanation and possible direct hydrogenolysis of C-C bonds. This work provides new insights into the catalytic mechanisms of RuO2 during SCWG of carbonaceous materials, along with the possibility of producing high yields of methane from MSW fractions.

Analysis of Hue Spectra During Storage of Pepper (Capsicum annuum)

Color information is widely used in non-destructive quality assessment of perishable horticultural produces. The presented work investigated color changes of pepper (Capsicum annuum L.) samples received from retail system. The effect of storage temperature (10±2°C and 24±4°C) on surface color and firmness was analyzed. Hue spectra was calculated using sum of saturations. A ColorLite sph850 (400-700nm) spectrophotometer was used as reference instrument. Dynamic firmness was measured on three locations of the surface: tip cap, middle and shoulder. Significant effects of storage conditions and surface location on both color and firmness were observed. Hue spectra responded sensitively to color development of pepper. Prediction model (PLS) was used to estimate dynamic firmess based on hue spectra. Accuracy was very different depending on the location. Firmness of the tip cap was predicted with the highest accuracy (RMSEP=0.0335). On the other hand, middle region cannot be used for such purpose. Due to the simplicity and rapid processing, analysis of hue spectra is a promising tool for evaluation of color in postharvest and food industry.

Responses of sawgrass and spikerush to variation in hydrologic drivers and salinity in Southern Everglades marshes

Aboveground net primary production (ANPP) by the dominant macrophyte and plant community composition are related to the changing hydrologic environment and to salinity in the southern Everglades, FL, USA. We present a new non-destructive ANPP technique that is applicable to any continuously growing herbaceous system. Data from 16 sites, collected from 1998 to 2004, were used to investigate how hydrology and salinity controlled sawgrass (Cladium jamaicense Crantz.) ANPP. Sawgrass live biomass showed little seasonal variation and annual means ranged from 89 to 639 gdw m)2. Mortality rates were 20–35% of live biomass per 2 month sampling interval, for biomass turnover rates of 1.3–2.5 per year. Production by C. jamaicense was manifest primarily as biomass turnover, not as biomass accumulation. Rates typically ranged from 300 to 750 gdw m)2 year)1, but exceeded 1000 gdw m)2 year)1 at one site and were as high as 750 gdw m)2 year)1 at estuarine ecotone sites. Production was negatively related to mean annual water depth, hydroperiod, and to a variable combining the two (depth-days). As water depths and hydroperiods increased in our southern Everglades study area, sawgrass ANPP declined. Because a primary restoration goal is to increase water depths and hydroperiods for some regions of the Everglades, we investigated how the plant community responded to this decline in sawgrass ANPP. Spikerush (Eleocharis sp.) was the next most prominent component of this community at our sites, and 39% of the variability in sawgrass ANPP was explained by a negative relationship with mean annual water depth, hydroperiod, and Eleocharis sp. density the following year. Sawgrass ANPP at estuarine ecotone sites responded negatively to salinity, and rates of production were slow to recover after high salinity years. Our results suggest that ecologists, managers, and the public should not necessarily interpret a decline in sawgrass that may result from hydrologic restoration as a negative phenomenon.

Flexible pavement layer moduli determination : an adaptive artificial neural network approach

The estimation of pavement layer moduli through the use of an artificial neural network is a new concept which provides a less strenuous strategy for backcalculation procedures. Artificial Neural Networks are biologically inspired models of the human nervous system. They are specifically designed to carry out a mapping characteristic. This study demonstrates how an artificial neural network uses non-destructive pavement test data in determining flexible pavement layer moduli. The input parameters include plate loadings, corresponding sensor deflections, temperature of pavement surface, pavement layer thicknesses and independently deduced pavement layer moduli.