Sentence examples for predictions of carbon from inspiring English sources
An accurate estimation of the past and current CO2 budget for the Earth's surface is needed for reliable predictions of carbon cycle changes under global warming conditions.
Site-specific descriptors (e.g., site productivity) that might help stratify the data and provide more accurate predictions of carbon pools will need to be applied in order to help refine our predictions of carbon accretion rates in particular locations.
While it might be feasible to provide model-based predictions of carbon stocks and sequestration rates, an ex-ante prediction including the driving factors market and policy is arguable.
Using FBA, in silico predictions of carbon, nitrogen, phosphorous, iron, and sulfur source utilization were compared to experimentally determined values for 38 enterobacterial strains spanning 23 genera for both aerobic and anaerobic conditions.
Our results suggest that efforts to incorporate these factors in ESMs should reduce current uncertainties associated with ESM predictions of carbon-climate feedbacks.
Results show property prediction capability with reasonable accuracy except for prediction of carbon dioxide concentration.
For a safe and economical design, prediction of carbon dioxide solubility by a trustworthy model is really essential.
Her research involves the monitoring and mitigation of contaminants in water resources; the measurement and prediction of carbon fluxes in terrestrial and subsurface environments; and the management, synthesis, and analysis of diverse multi-scale environmental datasets.
The focus of CFD simulations is to demonstrate the crucial role of intrinsic based heterogeneous reactions in the adequate prediction of carbon conversion rates.
The aim of this work is solubility prediction of carbon dioxide (CO2) in amino acid salt solutions as new absorbents over wide ranges of operating conditions, utilizing Artificial Neural Network (ANN) and Deshmukh Mather models.
In this study a new model based on adaptive neuro-fuzzy inference systems (ANFIS) is designed and developed for accurate prediction of carbon dioxide diffusivity in oils at elevated temperature and pressures.
