Biofuels, vehicle emissions, and urban air quality

2016 ◽  
Vol 189 ◽  
pp. 121-136 ◽  
Author(s):  
Timothy J. Wallington ◽  
James E. Anderson ◽  
Eric M. Kurtz ◽  
Paul J. Tennison

Increased biofuel content in automotive fuels impacts vehicle tailpipe emissions via two mechanisms: fuel chemistry and engine calibration. Fuel chemistry effects are generally well recognized, while engine calibration effects are not. It is important that investigations of the impact of biofuels on vehicle emissions consider the impact of engine calibration effects and are conducted using vehicles designed to operate using such fuels. We report the results of emission measurements from a Ford F-350 fueled with either fossil diesel or a biodiesel surrogate (butyl nonanoate) and demonstrate the critical influence of engine calibration on NOx emissions. Using the production calibration the emissions of NOx were higher with the biodiesel fuel. Using an adjusted calibration (maintaining equivalent exhaust oxygen concentration to that of the fossil diesel at the same conditions by adjusting injected fuel quantities) the emissions of NOx were unchanged, or lower, with biodiesel fuel. For ethanol, a review of the literature data addressing the impact of ethanol blend levels (E0–E85) on emissions from gasoline light-duty vehicles in the U.S. is presented. The available data suggest that emissions of NOx, non-methane hydrocarbons, particulate matter (PM), and mobile source air toxics (compounds known, or suspected, to cause serious health impacts) from modern gasoline and diesel vehicles are not adversely affected by increased biofuel content over the range for which the vehicles are designed to operate. Future increases in biofuel content when accomplished in concert with changes in engine design and calibration for new vehicles should not result in problematic increases in emissions impacting urban air quality and may in fact facilitate future required emissions reductions. A systems perspective (fuel and vehicle) is needed to fully understand, and optimize, the benefits of biofuels when blended into gasoline and diesel.

1997 ◽  
Vol 31 (10) ◽  
pp. 1497-1511 ◽  
Author(s):  
N. Moussiopoulos ◽  
P. Sahm ◽  
K. Karatzas ◽  
S. Papalexiou ◽  
A. Karagiannidis

2019 ◽  
Vol 8 (4) ◽  
pp. 42-59 ◽  
Author(s):  
Gwendoline l'Her ◽  
Myriam Servières ◽  
Daniel Siret

Based on a case study in Rennes, the article presents how a group of urban public actors re-uses methods and technology from citizen sciences to raise the urban air quality issue in the public debate. The project gives a group of inhabitants the opportunity to follow air quality training and proceed PM2.5µm measurements. The authors question the impact of the ongoing hybridisation between citizen science and urban public action on participants' commitment. The authors present how the use of PM2.5-sensors during 11 weeks led to a disengagement phenomenon, even if the authors observe a strong participation to workshops. These results come from an interdisciplinary methodology using observations, interviews, and data analyses.


2016 ◽  
Vol 91 ◽  
pp. 230-242 ◽  
Author(s):  
Congrong He ◽  
Branka Miljevic ◽  
Leigh R. Crilley ◽  
Nicholas C. Surawski ◽  
Jennifer Bartsch ◽  
...  

2014 ◽  
Vol 86 ◽  
pp. 58-67 ◽  
Author(s):  
Nicole R. Ramsey ◽  
Petra M. Klein ◽  
Berrien Moore

2013 ◽  
Vol 8 (3) ◽  
pp. 306-314 ◽  

The paper describes the development of a fast and easy-to-use qualitative tool for preliminary assessments of urban air quality related to road traffic. The tool is particularly aimed at the ability and budget of local government. It uses a novel interaction matrix-type methodology combined with mapping overlay, performed via a GIS. More specifically, the interaction matrix provides the weighting factors, which show the impact of each variable involved in a system on the target variable, air quality, as well as on the system as a whole. These weighting factors are used in the GIS to produce vulnerability maps. The maps visualise vulnerability to air pollution due to the combined effect of a number of interacting factors, and thus indicate areas susceptible to poor air quality. This results in a considerable reduction in computing time and complexity compared to the use of a sophisticated numerical model, as the user of the GIS tool only needs to perform mapping overlays in the GIS (using the previously derived weighting factors). The particular aim of this study was to compare two different methods for quantifying the interactions between variables in the matrix. The first method used constant coefficients, whose values are based on parametric studies performed using an advanced dispersion model or on good engineering judgement. The second method used a more sophisticated and versatile quantification of the interactions between variables, via analytical or semi-empirical relationships. In the latter method, the matrix was formulated computationally, so that the interaction weightings for different conditions can be obtained automatically. The technique was applied to the case study of an urban area with a high traffic throughput, in the UK. Two different interaction matrices were constructed for urban air quality linked to road traffic, based on the above methods. The GIS results based on both matrix methodologies were compared to the results of a more intensive dispersion numerical model in terms of pollutant dispersion patterns and hot spots. Both sets of results were shown to compare favourably with those of the numerical model. The results based on the more sophisticated matrix coding were found to be in closer agreement with those of the numerical model.


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