CARBOTRAF: A decision Support system for reducing pollutant emissions by adaptive traffic management

Traffic congestion with frequent “stop & go” situations causes substantial pollutant emissions. Black carbon (BC) is a good indicator of combustion-related air pollution and results in negative health effects. Both BC and CO2 emissions are also known to contribute significantly to global warming. Current traffic control systems are designed to improve traffic flow and reduce congestion. The CARBOTRAF system combines real-time monitoring of traffic and air pollution with simulation models for emission and local air quality prediction in order to deliver on-line recommendations for alternative adaptive traffic management. The aim of introducing a CARBOTRAF system is to reduce BC and CO2 emissions and improve air quality by optimizing the traffic flows. The system is implemented and evaluated in two pilot cities, Graz and Glasgow. Model simulations link traffic states to emission and air quality levels. A chain of models combines micro-scale traffic simulations, traffic volumes, emission models and air quality simulations. This process is completed for several ITS scenarios and a range of traffic boundary conditions. The real-time DSS system uses all these model simulations to select optimal traffic and air quality scenarios. Traffic and BC concentrations are simultaneously monitored. In this paper the effects of ITS measures on air quality are analysed with a focus on BC

Sodium ion interactions with aqueous glucose: Insights from quantum mechanics, molecular dynamics, and experiment

In the last several decades, significant efforts have been conducted to understand the fundamental reactivity of glucose derived from plant biomass in various chemical environments for conversion to renewable fuels and chemicals. For reactions of glucose in water, it is known that inorganic salts naturally present in biomass alter the product distribution in various deconstruction processes. However, the molecular-level interactions of alkali metal ions and glucose are unknown. These interactions are of physiological interest as well, for example, as they relate to cation-glucose cotransport. Here, we employ quantum mechanics (QM) to understand the interaction of a prevalent alkali metal, sodium, with glucose from a structural and thermodynamic perspective. The effect on B-glucose is subtle: a sodium ion perturbs bond lengths and atomic partial charges less than rotating a hydroxymethyl group. In contrast, the presence of a sodium ion significantly perturbs the partial charges of α-glucose anomeric and ring oxygens. Molecular dynamics (MD) simulations provide dynamic sampling in explicit water, and both the QM and the MD results show that sodium ions associate at many positions with respect to glucose with reasonably equivalent propensity. This promiscuous binding nature of Na + suggests that computational studies of glucose reactions in the presence of inorganic salts need to ensure thorough sampling of the cation positions, in addition to sampling glucose rotamers. The effect of NaCl on the relative populations of the anomers is experimentally quantified with light polarimetry. These results support the computational findings that Na + interacts similarly with a- and B-glucose

Modeling polysaccharides: present status and challenges

International audienc

A comparison and chemometric analysis of several molecular mechanics force fields and parameters sets applied to carbohydrates

International audienc