A qualitative tool combining an interaction matrix and a GIS to map vulnerability to traffic induced air pollution

Mavroulidou, Maria; Hughes, Susan; Hellawell, E. E.

doi:10.1016/j.jenvman.2003.12.002

Cited by 29 publications

(15 citation statements)

References 5 publications

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“…The remaining interactions were assigned values based on good engineering judgment as it was not possible to apply the dispersion model for their quantification. A detailed description of the methodology for air quality, applied to a small study area is given in [4]. Table 1.…”

Section: Constant Coefficient Matrixmentioning

confidence: 99%

“…They correspond to the constant and varying coefficient matrix methodologies respectively. The maps depict the vulnerability zones numbered in ascending order (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12) from the lowest to highest air pollutant concentrations. They are based on a "worst-case scenario", which corresponds to the maximum possible CO ground level concentrations for ranges of values of each variable representative of those encountered in the study area.…”

Section: Geographic Information Systemmentioning

confidence: 99%

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A comparison of two interaction matrix coding techniques used in a GIS-based tool for air quality assessment

2013

Global NEST Journal

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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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Section: Constant Coefficient Matrixmentioning

confidence: 99%

Section: Geographic Information Systemmentioning

confidence: 99%

A comparison of two interaction matrix coding techniques used in a GIS-based tool for air quality assessment

2013

Global NEST Journal

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“…The result showed that vehicular emission management should include both transportation policies and air pollution control technologies. Mavroulidou et al (2004) presented a tool for assessment of urban air quality due to vehicular emissions. The tool was easy to use with visual output.…”

Section: Introductionmentioning

confidence: 99%

An evaluation of improvements in the air quality of Beijing arising from the use of new vehicle emission standards

Jin

Gao

et al. 2011

Environ Monit Assess

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An innovative approach of mean emission by vehicle type was used in this paper to assess the impact of new vehicle emission standards in Beijing, China during the period of 2000-2005. It was found that CO and NO(x) emissions decreased by 48% and 23%, respectively, from Type O (before 2000) to Type I (year 2000) vehicles. The reductions from Type O to Type II (year 2002) vehicles were 85% and 73% for CO and NO(x), respectively. When all three types of vehicles (Types O, I and II) are combined, the annual per vehicle CO emissions decreased from 586 kg per vehicle per year in 2000 to 324 kg per vehicle per year in 2005, while that of NO(x) decreased from 66.9 to 43.4 kg per vehicle per year, which was mainly resulted from the impact of stringent new vehicle emission standards implemented in years 2000 and 2002. However, the vehicle population increased by 70% during the same time period, which offset the impact of cleaner vehicles. Thus, the total vehicle emission decreased little for CO (885,000 tons in 2000, 837,000 tons in 2005) and even increased slightly for NO(x) (101,000 and 112,000 tons in 2000 and 2005, respectively). The ambient concentrations of CO decreased significantly throughout 2000-2005, the same trend was not observed for NO(2). Correlation analysis (grey correlation and Pearson correlation) between the annual vehicle emissions and annual concentrations of CO, the annual NO(x) emission and annual NO(2) concentration indicated that the implementation of new vehicle emission standards was associated with the abatement of ambient CO and NO(2) concentrations in Beijing.

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“…Thus the methodology combined system analysis theory concepts with interaction matrices and accounted for the relative importance of each variable in a system. In 2004, Mavroulidou et al (2004) applied the modified interaction matrix to assess air quality problems. In this research, the interaction matrix was combined with Geographic Information System (GIS) mapping overlay, in the development of a tool to provide an initial impression of local air quality.…”

Section: Introductionmentioning

confidence: 99%

“…This paper presents further development of the interaction matrix methodology used by Mavroulidou et al (2004) to enable a more rigorous quantification of the interactions assigned in the matrix and further evaluation of the matrix technique. The modification consists of incorporating varying matrix interactions (as opposed to the constant coefficients used in Mavroulidou et al (2004)).…”

Section: Introductionmentioning

confidence: 99%

Developing the interaction matrix technique as a tool assessing the impact of traffic on air quality

Mavroulidou¹,

Hughes²,

Hellawell³

2007

Journal of Environmental Management

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A qualitative tool combining an interaction matrix and a GIS to map vulnerability to traffic induced air pollution

Cited by 29 publications

References 5 publications

A comparison of two interaction matrix coding techniques used in a GIS-based tool for air quality assessment

A comparison of two interaction matrix coding techniques used in a GIS-based tool for air quality assessment

An evaluation of improvements in the air quality of Beijing arising from the use of new vehicle emission standards

Developing the interaction matrix technique as a tool assessing the impact of traffic on air quality

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