Our society currently faces three challenges, including resource depletion, waste accumulation and environmental degradation, leading to rapidly escalating raw material costs and increasingly expensive and restrictive waste disposal legislation. This work aims to produce clean solid biofuel from high moisture content waste biomass (bio-waste) with high nitrogen (N)/chlorine (Cl) content by mild hydrothermal (HT) conversion processes. The newest results are summarized and discussed in terms of the mechanical dewatering and upgrading, dechlorination, denitrification and coalification resulting from the HT pretreatment. Moreover, both the mono-combustion and co-combustion characteristics of the solid fuel are reviewed by concentrating on the pollutants emission control, especially the NO emission properties. In addition, the feasibility of this HT solid biofuel production process is also discussed in terms of “Energy Balance and economic viability”. As an alternative to dry combustion/dry pyrolysis/co-combustion, the HT process, combining the dehydration and decarboxylation of a biomass to raise its carbon content aiming to achieve a higher calorific value, opens up the field of potential feedstock for lignite-like solid biofuel production from a wide range of nontraditional renewable and plentiful wet agricultural residues, sludge and municipal wastes. It would contribute to a wider application of HT pretreatment bio-wastes for safe disposal and energy recycling.
Moisture diffusivity of thermal insulation materials as a function of moisture content, YM, Ytong Multipor; MW-HB, hydrophobic mineral wool; MW-HLH, hard hydrophilic mineral wool; MW-HLS, soft hydrophilic mineral wool. ► Complete sets of heat and moisture transport and storage properties of five thermal insulation materials are presented. ► All material parameters are measured in dependence on moisture content. ► Hydrophobic mineral wool and expanded polystyrene are selected as reference materials. ► Two types of hydrophilic mineral wool suitable for interior thermal insulation systems are analyzed. ► A thermal insulation board on the basis of autoclaved aerated concrete is investigated. Computational models of heat and moisture transport are frequently used in calculating energy gains and losses in buildings. However, any model can provide reliable information only in the case that the quality of input data is adequate. This is not always true because the standard lists of thermal and hygric parameters given by the producers as well as the material databases included in the simulation tools are usually far from complete. In this paper, we present the measurements of complete sets of heat and moisture transport and storage parameters of selected thermal insulation materials in dependence on moisture content. Two common thermal insulation materials, namely hydrophobic mineral wool and expanded polystyrene, are selected as reference materials. Two types of hydrophilic mineral wool and an autoclaved-aerated-concrete thermal insulation board are the representatives of prospective materials which appeared on the market within the last couple of years. The studied material parameters include bulk density, matrix density, porosity, saturation moisture content, thermal conductivity, specific heat capacity, moisture diffusivity, water vapor diffusion coefficient, sorption isotherm, and water retention curve.
Data from the satellite-based Special Sensor Microwave Imager (SSM/I) show that the total atmospheric moisture content over oceans has increased by 0.41 kg/m² per decade since 1988. Results from current climate models indicate that water vapor increases of this magnitude cannot be explained by climate noise alone. In a formal detection and attribution analysis using the pooled results from 22 different climate models, the simulated "fingerprint" pattern of anthropogenically caused changes in water vapor is identifiable with high statistical confidence in the SSM/I data. Experiments in which forcing factors are varied individually suggest that this fingerprint "match" is primarily due to human-caused increases in greenhouse gases and not to solar forcing or recovery from the eruption of Mount Pinatubo. Our findings provide preliminary evidence of an emerging anthropogenic signal in the moisture content of earth's atmosphere.
Methane adsorption capacity is a key factor in determining shale gas in place (GIP) – requiring that it is determined under in situ moisture conditions. Current methods may be insufficient to investigate these exact characteristics when applied to actual reservoirs with high or variable moisture contents. We propose a heating and cooling (HC) method to prepare shale samples to arbitrary moisture contents (M up to 10%). A series of CH adsorption experiments on two different types of shale are conducted as a function of M at 35 °C, 45 °C, and 55 °C, and at a CH pressure of up to 10 MPa. Experimental results indicate that the methane sorption capacity versus moisture content curves exhibit a linear decreasing stage, a flat stage and a convex decreasing stage, separated by two threshold moisture contents. The lower moisture content threshold (M ) represents coverage of the entire hydrophilic surface by a monolayer of water. The upper moisture content threshold (M ) is the point at which no methane is adsorbed on the surface of the clay pores and adsorption capacity is further reduced as moisture content is increased. The linear stage with M up to the M is mainly dominated by the competition between water and methane for adsorption sites on the surface of clay pores. Slope value of this stage are affected by pressure, temperature and shale compositions. The flat stage represents that the moisture content has negligible effect on shale adsorption capacity for M in the range M to M . Methane adsorption capacity decreases in a convex manner above M , suggesting water condensation in organic pores as the surface area for methane adsorption is reduced by water blocking. A conceptual Bi-Langmuir model is presented to represent the crucial effects of moisture content on methane adsorption capacity including accurate estimations of original GIP under different reservoir conditions.
► The main factors affecting the stability and maturity of composting were studied. ► The aeration rate was the major factor influencing the stability of compost. ► The initial C/N ratio mainly influenced the maturity of the final compost. ► Moisture content can affect the quality of compost but not significantly. ► Recommendation for composting is an aeration rate of 0.48 L kg DM min , a C/N ratio of 18 and moisture contents of 65–75%. To estimate the order of importance of factors affecting the stability and maturation of compost, pig feces and corn stalks were co-composted at different aeration rates (AR: 0.24, 0.48, 0.72 L kg dry matter (DM) min ), C/N ratios (15, 18, 21), and moisture contents (MC: 65%, 70%, 75%). The thermophilic phase with all treatments was long enough to meet sanitation requirements. The oxygen content and N losses increased with increasing AR, but no significant differences were observed between the moderate and high treatments. The compost with the lowest initial C/N ratio was significantly different from the other treatments and had the lowest germination index (53–66%). AR was the main factor influencing compost stability, while the C/N ratio mainly contributed to compost maturity, and the MC had an insignificant effect on the compost quality. The recommended parameters for composting are an AR of 0.48 L kg DM min and a C/N ratio of 18 with MCs of 65–75%.
► Hyperspectral imaging as moisture content predictors of prawn. ► Prawns were extracted from background using spatial features of hyperspectral imaging. ► Moisture contents were determined using spectral features of hyperspectral imaging. ► SPA was first used for wavelength selection in hyperspectral imaging analysis. ► Moisture content distributions were visualized at different dehydration periods. Because the shape of prawn is not round, spectroscopy instruments cannot measure the spectra of the whole prawn without containing background information. In this study, an online hyperspectral imaging system in the spectral region of 380–1100 nm was developed to determine the moisture content of prawns at different dehydrated levels. Hyperspectral images of prawns were acquired at different dehydration periods. The spectra of prawns then were extracted from hyperspectral images based on ‘Manual Prawn Mask’ and ‘Automatic Prawn Mask’, respectively. Spectral data were analyzed using partial least squares regression (PLSR) and least-squares support vector machines (LS-SVM) to establish the calibration models, respectively. Successive projections algorithm (SPA) was first applied for the optimal wavelength selection in the hyperspectral image analysis. Out of 482 wavelengths, only twelve wavelengths (428, 445, 544, 569, 629, 672, 697, 760, 827, 917, 958, and 999 nm) were selected by SPA as the optimum wavelengths for moisture prediction. Based on these optimum wavelengths, a multiple linear regression (MLR) calibration model was established and used to obtain the moisture distribution of each prawn. The overall results of this study revealed the potentiality of hyperspectral imaging as an objective and non-destructive method to obtain the content and distribution of moisture of prawns whose shapes are not round.
Vegetation moisture content is an important early indicator of forest drought stress, disease and fire risk. Existing remote sensing techniques to measure biochemical properties of vegetation, such as Equivalent Water Thickness (EWT), are limited by an inability to differentiate canopy and understorey properties and are influenced by variations in canopy structure. By providing a range-resolved estimate of reflectance, laser scanner measurements have the potential to overcome these limitations. Dual-wavelength laser scanning can provide an active measurement of reflectance from which spectral indices can be derived that are insensitive to range, incidence angle and scattering area of the target within the laser beam, factors that make exploiting single-wavelength laser scanner intensity data difficult. This study demonstrates the potential of dual-wavelength laser scanning for measurement of leaf biochemical properties, through determining the relationship between a laser-scanner-derived spectral index, using near infrared (1063 nm) and middle infrared (1545 nm) wavelengths, and the EWT of individual leaves. The suitability and sensitivity of the index is tested using a leaf optical properties model (PROSPECT-5) and the method is tested experimentally under laboratory conditions using the Salford Advanced Laser Canopy Analyser. A strong relationship (R = 0.8, RMSE = 0.0069 g cm ) was found between a normalised ratio of the two wavelengths and measured EWT of leaf samples. The relationship corresponds well to that predicted by modelling. However, the experimental data also revealed significant spatial variability in the index value across individual leaves, suggesting heterogeneity in moisture distribution at within-leaf scales. The study suggests significant potential for using dual-wavelength and multispectral laser scanning for measuring vegetation biochemical properties. ► Dual-wavelength LiDAR shows potential to improve estimates of canopy biochemistry. ► A Laser-derived spectral index is strongly related to leaf Equivalent Water Thickness. ► Experimental results match those predicted by leaf reflectance modelling. ► An application of the Salford Advanced Laser Canopy Analyser is demonstrated.
The equilibrium moisture content (EMC) of raw lignocellulosic biomass, along with four samples subjected to thermal pretreatment, was measured at relative humidities ranging from 11% to 97% at a constant temperature of 30 °C. Three samples were prepared by treatment in hot compressed water by a process known as wet torrefaction, at temperatures of 200, 230, and 260 °C. An additional sample was prepared by dry torrefaction at 300 °C. Pretreated biomass shows EMC below that of raw biomass. This indicates that pretreated biomass, both dry and wet torrefied, is more hydrophobic than raw biomass. The EMC results were correlated with a recent model that takes into account additional non-adsorption interactions of water, such as mixing and swelling. The model offers physical insight into the water activity in lignocellulosic biomass.
In recent years, nitrogen (N) loss from upland fields has become one of the most important sources for agricultural nonpoint source (NPS) pollution. Understanding the relationships between soil hydrological processes and N loss in NPS pollution is vital for controlling the agricultural NPS pollution in upland fields. The objective of this study was to analyze the interaction of N loss with different moisture conditions in the freeze-thaw zone. The semi-distributed hydrologic model Soil and Water Assessment Tool (SWAT) was used in this study to simulate runoff and different forms of N loss, which provided a basis for analyzing characteristics of N loss in the study region. Results showed that the soil moisture content was an important factor affecting N loss in the study region. Different forms of N loss were also analyzed and it was found that N loss occurred primarily in the form of organic-N, which is likely due to the dominant role of erosion-induced pollution. This study provides useful information for preventing NPS pollution within the study region.
Pasta aside from bread is the most consumed cereal-based product in the world. Its taste and cooking ease makes it the basis of many cuisines. The pasta dough formed by mixing flour and water is extruded through an extrusion die to mould the appropriate pasta form and is dried to obtain a stable product. The concentration of moisture in the pasta dough is a one of key parameters determining the final quality of the product. Monitoring the moisture content of pasta after extrusion is also critically important. It enables a selection of suitable drying conditions that ensure the appropriate parameters of pasta, such as texture, color and taste, are met. A method for the quantitative determination of moisture content in pasta dough and in pasta based on the partial least squares treatment of infrared spectra registered using a single-reflection attenuated total reflectance diamond accessory is described. Results of a similar quality were found using models derived from near infrared spectra obtained in a diffuse reflectance mode and slightly worse based on Raman spectra. Relative standard errors of prediction calculated for moisture quantification by ATR/NIR/Raman techniques amounted to 2.54/3.16/5.56% and 2.15/3.32/5.67%, for calibration and validation sets, respectively. The proposed procedures can be used for fast and efficient pasta moisture quantification and may replace the current, more laborious methods used.