Life Cycle Assessment of Polyol Fuel from Corn Stover via Fast Pyrolysis and Upgrading

The purpose of this study is to evaluate the fossil energy consumption and the greenhouse gas (GHG) emissions of polyol fuel produced via corn stover fast pyrolysis and bio-oil upgrading based on life cycle assessment (LCA). The required material and energy inputs involved in the unit processes of LCA are taken from Aspen Plus simulation models established according to a demonstration plant with annual polyol output of 1000 tonnes. The eBalance software with a Chinese Life Cycle Database (CLCD) is employed to perform this task. The research results show the net fossil energy input (FEI) and the net global warming potential (GWP) of polyol fuel are respectively 0.760 MJ and 0.0444 kgCO_2,eq per MJ energy output under the proposed production pathway. Compared to petroleum-based gasoline and diesel, the net FEI of polyol fuel reduces by 42.9% and 42.2% respectively and the net GWP of polyol fuel decreases by 55.1% and 56.9% accordingly. Sensitivity analysis indicates the data uncertainty of the polyol yield and the electricity consumption for bio-oil production has significant impact on the GHG emissions. The polyol fuel is expected to partly replace petroleum-based fuels

Reflectance Prediction Modelling for Residual-Based Hyperspectral Image Coding - Fig 3

<p><b>The distribution of spectral reflectance in different bands: (a) and (b) the effective spectral reflectance of 20 pixels randomly selected in the range of 61 bands (400nm to 1000nm) of two HS images namely ‘Soil’ and ‘Strawberry’ captured by the Brimrose HS camera at Griffith University.</b></p

Urban expansion patterns of 291 Chinese cities, 1990–2015

<p>China has experienced rapid and massive urban expansion in recent decades. To address the opportunities and challenges posed by urbanization, it is important to investigate this process. Although many studies have characterized China’s urbanization, mainly based on individual cities or urban agglomerations, few studies have compared the urban expansion patterns among cities of different regions and sizes at a national scale. Additionally, the source of the newly developed urban land has largely been ignored in previous research. To fill these gaps, we provide a comprehensive view of the growth patterns of 291 Chinese cities during 1990–2015, quantifying the rates, spatial forms, and corresponding landscape characteristics of the urban expansion. More importantly, we further investigate what their new urban land is converted from. Key findings include: (1) the annual expansion (AE) and annual growth rate (AGR) of all 291 cities were 1869.81 km² and 4.81% during 1990–2015; (2) cropland and rural settlements were the predominant source, accounting for 65.22% and 17.49% of the new urban land during 1990–2015; (3) edge-expansion was the dominant growth form for most cities, followed by infilling and leapfrogging growth; and (4) the landscape characteristics of the occupied cropland differed across various cities.</p

A Novel Large-Scale Temperature Dominated Model for Predicting the End of the Growing Season

<div><p>Vegetation phenology regulates many ecosystem processes and is an indicator of the biological responses to climate change. It is important to model the timing of leaf senescence accurately, since the canopy duration and carbon assimilation are strongly determined by the timings of leaf senescence. However, the existing phenology models are unlikely to accurately predict the end of the growing season (EGS) on large scales, resulting in the misrepresentation of the seasonality and interannual variability of biosphere–atmosphere feedbacks and interactions in coupled global climate models. In this paper, we presented a novel large-scale temperature dominated model integrated with the physiological adaptation of plants to the local temperature to assess the spatial pattern and interannual variability of the EGS. Our model was validated in all temperate vegetation types over the Northern Hemisphere. The results indicated that our model showed better performance in representing the spatial and interannual variability of leaf senescence, compared with the original phenology model in the Integrated Biosphere Simulator (IBIS). Our model explained approximately 63% of the EGS variations, whereas the original model explained much lower variations (coefficient of determination R² = 0.01–0.18). In addition, the differences between the EGS reproduced by our model and the MODIS EGS at 71.3% of the pixels were within 10 days. For the original model, it is only 26.1%. We also found that the temperature threshold (TcritTm) of grassland was lower than that of woody species in the same latitudinal zone.</p></div

Structure–Reactivity Relationship in Fast Pyrolysis of Lignin into Monomeric Phenolic Compounds

The structure–reactivity relationship in fast pyrolysis of lignin for monomeric phenolic compounds was studied on seven lignins from hardwood, softwood, and grass. The distribution of elements, functional groups, phenylpropane units, and interunit linkage bonds varied greatly across the lignins. Lignins from hardwood and grass prepared with mild conditions presented more C–O linkages. Pyrolysis–gas chromatography/mass spectrometry showed that the cleavage of unstable C–O linkages dominated the pyrolysis reaction at low temperatures, and the total yields of monomers peaked at 700 °C for most lignins. 4-Vinylphenol produced from acid extracted corn stalk lignin reached up to 4.77 wt % at 700 °C. Pyrolysis of grass lignins and woody lignins, which had more unstable C–O linkages, exhibited higher total yields of monomers. The pyrolysis behavior of lignin at low temperatures is closely related to its structural characteristics. Pyrolyzed at 500 °C, the total yields of monomeric aromatics were highly linearly correlated with the frequencies of C–O linkages (<i>R</i>² = 0.86). This work demonstrates the significance of selecting the right lignin for producing monomeric aromatic compounds

Vegetation distribution map of the Northern Hemisphere retrieved from the V005 MODIS Land Cover Type Product (MCD12Q1).

<p>Grey areas are either excluded vegetation types, such as croplands, or areas with no seasonal cycle detectable by satellite. The maps were created by the ArcMap 9.3. The data is freely provided by the Land Processes Distributed Active Archive Center (LP DAAC) (<a href="https://lpdaac.usgs.gov/data_access/data_pool" target="_blank">https://lpdaac.usgs.gov/data_access/data_pool</a>.).</p

Average metrics of QRC's top 20 papers versus .

<p>The vertical dashed line at marks the setting where citation count and the SJR score are approximately maximized.</p

Computational time requirement of the proposed RPM scheme with respect to HEVC (left) and the percentage of reference from the predicted spectral band i.e. CIW band and the 2nd reference band by the proposed scheme and the HEVC respectively.

<p>Computational time requirement of the proposed RPM scheme with respect to HEVC (left) and the percentage of reference from the predicted spectral band i.e. CIW band and the 2nd reference band by the proposed scheme and the HEVC respectively.</p

Cumulative degree distributions in the Econophysics Forum data with respect to various actions for users, papers, and authors.

<p>The editor was removed from the user upload distribution for the sake of clarity.</p

Spatial pattern of the mean dates for the EGS in the Northern Hemisphere for 2001–2010.

<p>(a) The dates derived from the MODIS product; (b) the EGS dates derived from the original model; (c) the EGS dates derived from our model. The maps were created by the ArcMap 9.3.</p