Engineering topics

Bell, S.

Publications and source records attributed to Bell, S..

3 records

DOE OSTI2020

Management opportunities for soil carbon sequestration following agricultural land abandonment

The widespread historical and ongoing abandonment of agricultural lands worldwide presents important opportunities for promoting climate change mitigation through carbon sequestration. The default management outcome of abandonment is natural regeneration through ecological succession. However, several different management strategies and new land uses for abandoned agricultural lands have been recommended by the scientific community in recent years. This paper reviews the foremost proposed strategies and compares their soil carbon sequestration potentials. Six major categories have been proposed globally. Each proposal has positive and negative outcomes depending on site-specific factors and management objectives. Accordingly, no single strategy is ideal in all scenarios and a combination of strategies addresses multiple rural development goals concurrently. A combination of passive and active management techniques is the most effective approach for maximizing soil carbon sequestration over large geographic scales, while other strategies can be designed to also promote low-carbon land use practices and fossil fuel substitution. The implications of each proposal highlighted here demonstrates the positive role that abandoned agricultural lands can serve in climate change mitigation efforts, supporting policymakers tasked with planning the future of regions undergoing abandonment.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2000

Neural network recognition of chemical class information in mobility spectra obtained at high temperatures

A minimal neural network was applied to a large library of high-temperature mobility spectra drawn from 16 chemical classes including 154 substances with 2000 spectra at various concentrations. A genetic algorithm was used to create a representative subset of points from the mobility spectrum as input to a cascade-type back-propagation network. This network demonstrated that significant information specific to chemical class was located in the spectral region near the reactant ions. This network failed to generalize the solution to unfamiliar compounds necessitating the use of complete spectra in network processing. An extended back-propagation network classified unfamiliar chemicals by functional group with a mean for average values of 0.83 without sulfides and 0.79 with sulfides. Further experiments confirmed that chemical class information was resident in the spectral region near the reactant ions. Deconvolution of spectra demonstrated the presence of ions, merged with the reactant ion peaks that originated from introduced samples. The ability of the neural network to generalize the solution to unfamiliar compounds suggests that these ions are distinct and class specific.

NASA Discipline Environmental Health↗

NASA NTRS1999

Classification of ion mobility spectra by functional groups using neural networks

Neural networks were trained using whole ion mobility spectra from a standardized database of 3137 spectra for 204 chemicals at various concentrations. Performance of the network was measured by the success of classification into ten chemical classes. Eleven stages for evaluation of spectra and of spectral pre-processing were employed and minimums established for response thresholds and spectral purity. After optimization of the database, network, and pre-processing routines, the fraction of successful classifications by functional group was 0.91 throughout a range of concentrations. Network classification relied on a combination of features, including drift times, number of peaks, relative intensities, and other factors apparently including peak shape. The network was opportunistic, exploiting different features within different chemical classes. Application of neural networks in a two-tier design where chemicals were first identified by class and then individually eliminated all but one false positive out of 161 test spectra. These findings establish that ion mobility spectra, even with low resolution instrumentation, contain sufficient detail to permit the development of automated identification systems.

Non-NASA Center↗