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

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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Analysis of the Impact of Road Traffic on the Urban Air Quality

10.21203/rs.3.rs-139784/v1 ◽

2021 ◽

Author(s):

Qi Wang ◽

Haixia Feng ◽

Haiying Feng ◽

Jian Li ◽

Erwei Ning

Keyword(s):

Air Quality ◽

Road Network ◽

Road Traffic ◽

Urban Air Quality ◽

Network Density ◽

Urban Air ◽

Traffic Planning ◽

The Road ◽

Bus Network ◽

The Impact

Abstract With a focus on the hot topics of traffic congestion and smog (air quality), in this study, the impact of road traffic on urban air quality was the first quantitatively analyzed based on the aerosol optical thickness (AOD) and geographical weighted regression (GWR) models, including the road network density, road area occupancy, intersection number, and bus network density. The main research conclusions are as follows. There is a strong positive correlation between the peak congestion delay index (PCDI) and air quality. Based on the GWR model, AOD has high correlations with four road network traffic characteristic parameters, and these correlations are much higher than ordinary linear regression, that is, GWR refines the local spatial changes in the AOD and the road parameters. The correlation was mainly positive. The correlation between AOD and the road area occupancy was the highest, and the correlations between PM2.5 and the density of the bus network and the number of intersections were higher than those with the road network density. Thus, bus route planning, bus emission reduction, road network planning, and signal timing (intersection) have a greater impact on air quality, especially in areas with traffic jams. This study has a certain guiding significance for traffic planning and traffic control, and it provides support and a basis for traffic planning and control.

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Comparing different approaches for assessing the impact of COVID-19 lockdown on urban air quality in Reading, UK

Atmospheric Research ◽

10.1016/j.atmosres.2021.105730 ◽

2021 ◽

pp. 105730

Author(s):

Said Munir ◽

Zhiwen Luo ◽

Tim Dixon

Keyword(s):

Air Quality ◽

Urban Air Quality ◽

Urban Air ◽

The Impact

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The Potential Impacts of Electric Vehicles on Urban Air Quality in Shanghai City

Sustainability ◽

10.3390/su13020496 ◽

2021 ◽

Vol 13 (2) ◽

pp. 496

Author(s):

Xiaojian Hu ◽

Nuo Chen ◽

Nan Wu ◽

Bicheng Yin

Keyword(s):

Air Quality ◽

Electric Vehicles ◽

Public Transportation ◽

Road Traffic ◽

Urban Air Quality ◽

Urban Air ◽

Vehicular Emissions ◽

Potential Reduction ◽

Efficient Measure ◽

Shanghai City

The Shanghai government has outlined plans for the new vehicles used for the public transportation, rental, sanitation, postal, and intra-city freight to be completely powered by electricity by 2020. This paper analyzed the characteristics of vehicle emissions in Shanghai in the past five years. The potential reduction in road traffic related emissions due to the promotion and application of electric vehicle in Shanghai was evaluated. The potential reduction was quantified by vehicular emissions. The vehicular emissions inventories are calculated by the COPERT IV model under the different scenarios, of which the results indicate that promoting electric vehicles is the efficient measure to control all road traffic related emissions and improve urban air quality. The results also provided basis and support for making policies to promote and manage electric vehicles.

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Assessing the impact of the New Athens airport to urban air quality with contemporary air pollution models

Atmospheric Environment ◽

10.1016/s1352-2310(96)00283-x ◽

1997 ◽

Vol 31 (10) ◽

pp. 1497-1511 ◽

Cited By ~ 23

Author(s):

N. Moussiopoulos ◽

P. Sahm ◽

K. Karatzas ◽

S. Papalexiou ◽

A. Karagiannidis

Keyword(s):

Air Pollution ◽

Air Quality ◽

Urban Air Quality ◽

Urban Air ◽

The Impact ◽

Air Pollution Models

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Citizen as Sensors' Commitment in Urban Public Action

International Journal of E-Planning Research ◽

10.4018/ijepr.2019100103 ◽

2019 ◽

Vol 8 (4) ◽

pp. 42-59 ◽

Cited By ~ 1

Author(s):

Gwendoline l'Her ◽

Myriam Servières ◽

Daniel Siret

Keyword(s):

Air Quality ◽

Citizen Science ◽

Urban Air Quality ◽

Urban Air ◽

The Public ◽

Public Action ◽

Quality Issue ◽

Data Analyses ◽

The Impact

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.

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