scholarly journals The impacts of road traffic on urban air quality in Jinan based GWR and remote sensing

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qi Wang ◽  
Haixia Feng ◽  
Haiying Feng ◽  
Yue Yu ◽  
Jian Li ◽  
...  
Keyword(s):  
Air Quality ◽  
Road Network ◽  
Road Traffic ◽  
Intersection Number ◽  
Urban Air Quality ◽  
Network Density ◽  
Urban Air ◽  
Strong Positive Correlation ◽  
The Road ◽  
Bus Network

AbstractTraffic congestion and smog are hot topics in recent years. This study analyzes the impacts of road traffic characteristic parameters on urban air quality quantitatively based on aerosol optical thickness (AOD) and geographical weighted regression (GWR) models, including the road network density, road area occupancy, intersection number, and bus network density as main factors. There are some major research findings. Firstly, there exists a strong positive correlation between the peak congestion delay index (PCDI) and air quality, the correlation has R2 values of up to 0.4962 (R 0.70). Secondly, GWR refines the local spatial changes in the AOD and the road parameters, and the correlation R2 based GWR model all above 0.6. The correlation between AOD and the road area occupancy was the highest, and the correlations with the bus network density and the intersections number were higher than that with the road network density. Thus, bus route planning, bus emission reduction, road network planning, and signal timing (at intersections) have a greater impact on air quality than other policy, especially in areas with traffic jams. The results of this study could provide theoretical support for traffic planning and traffic control, and is promising in practice.

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

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.

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

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.

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

2013 ◽  
Vol 8 (3) ◽  
pp. 306-314 ◽  
Keyword(s):  
Air Quality ◽  
Numerical Model ◽  
Road Traffic ◽  
Pollutant Dispersion ◽  
Urban Air Quality ◽  
Interaction Matrix ◽  
Urban Air ◽  
Weighting Factors ◽  
The Matrix ◽  
The Impact

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.

scholarly journals Planning Structure As A Road Traffic Pollution Differentiation Factor: A Case Study Of Nur-Sultan

2021 ◽  
Vol 14 (3) ◽  
pp. 6-13
Author(s):  
A. Zh. Abilov ◽  
M. A. Anzorova ◽  
V. R. Bityukova ◽  
A. G. Makhrova ◽  
A. A. Khojikov ◽  
...  
Keyword(s):  
Road Network ◽  
Road Traffic ◽  
Spatial Differentiation ◽  
Road Transport ◽  
Middle Part ◽  
Transport Infrastructure ◽  
Network Density ◽  
The Road ◽  
High Level ◽  
The City

The article deals with the problem of spatial differentiation of road transport pollution due to the planning structure changes in the new capital of Kazakhstan. The purpose of the work is to study territorial differences in from vehicles Nur-Sultan from vehicles and to identify the role of embodied planning measures among the main factors of its differentiation. The research methodology included the analysis of 1) the city functions and planning structure transformation as well as the buildings and road network density and concentration; 2) traffic speed and intensity, emissions and their distribution areas for each street.The analysis showed that since 1997, when Nur-Sultan received the capital status, it has grown 3 times in the area, 3.5 times in population, and 6 times in the level of motorization. However, the volume of traffic emissions in the city increased only 2 times, largely due to the development of the planning structure and configuration of the road network. The development of a second center in the new part of the city along with the decrease in the barrier function of the river and transport transit because of the faster construction of transport infrastructure led to an increase in the density of the road network by more than 2 times while reducing the density of emissions in the city center by 2.25 times. For the rest of the territory, despite different growth rates in the road network density, the density of emissions steadily decreases from the center to the periphery. However, several locations with a high level of pollution are still present in the middle part, while on the outskirts of the city there are blocks of estate-type houses with low-quality roads, which hinder the development of public transport.

scholarly journals A very high-resolution assessment and modelling of urban air quality

2020 ◽  
Vol 20 (2) ◽  
pp. 625-647 ◽  
Author(s):  
Tobias Wolf ◽  
Lasse H. Pettersson ◽  
Igor Esau
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
High Resolution ◽  
Road Traffic ◽  
Urban Air Quality ◽  
City Centre ◽  
Urban Air ◽  
Wood Burning ◽  
The City ◽  
Very High

Abstract. Urban air quality is one of the most prominent environmental concerns for modern city residents and authorities. Accurate monitoring of air quality is difficult due to intrinsic urban landscape heterogeneity and superposition of multiple polluting sources. Existing approaches often do not provide the necessary spatial details and peak concentrations of pollutants, especially at larger distances from monitoring stations. A more advanced integrated approach is needed. This study presents a very high-resolution air quality assessment with the Parallelized Large-Eddy Simulation Model (PALM), capitalising on local measurements. This fully three-dimensional primitive-equation hydrodynamical model resolves both structural details of the complex urban surface and turbulent eddies larger than 10 m in size. We ran a set of 27 meteorological weather scenarios in order to assess the dispersion of pollutants in Bergen, a middle-sized Norwegian city embedded in a coastal valley. This set of scenarios represents typically observed weather conditions with high air pollution from nitrogen dioxide (NO2) and particulate matter (PM2.5). The modelling methodology helped to identify pathways and patterns of air pollution caused by the three main local air pollution sources in the city. These are road vehicle traffic, domestic house heating with wood-burning fireplaces and ships docked in the harbour area next to the city centre. The study produced vulnerability maps, highlighting the most impacted districts for each weather and emission scenario. Overall, the largest contribution to air pollution over inhabited areas in Bergen was caused by road traffic emissions for NO2 and wood-burning fireplaces for PM2.5 pollution. The effect of emission from ships in the port was mostly restricted to the areas close to the harbour and moderate in comparison. However, the results have contributed to implementation of measures to reduce emissions from ships in Bergen harbour, including provision of shore power.

scholarly journals Meta-modeling of a simulation chain for urban air quality

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
J. K. Hammond ◽  
R. Chen ◽  
V. Mallet
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Road Traffic ◽  
Low Cost ◽  
Urban Air Quality ◽  
Multiple Models ◽  
Urban Air ◽  
Dynamic Traffic ◽  
Reduced Basis ◽  
Meta Modeling

Abstract Urban air quality simulation is an important tool to understand the impacts of air pollution. However, the simulations are often computationally expensive, and require extensive data on pollutant sources. Data on road traffic pollution, often the predominant source, can be obtained through sparse measurements, or through simulation of traffic and emissions. Modeling chains combine the simulations of multiple models to provide the most accurate representation possible, however the need to solve multiple models for each simulation increases computational costs even more. In this paper we construct a meta-modeling chain for urban atmospheric pollution, from dynamic traffic modeling to air pollution modeling. Reduced basis methods (RBM) aim to compute a cheap and accurate approximation of a physical state using approximation spaces made of a suitable sample of solutions to the model. One of the keys of these techniques is the decomposition of the computational work into an expensive one-time offline stage and a low-cost parameter-dependent online stage. Traditional RBMs require modifying the assembly routines of the computational code, an intrusive procedure which may be impossible in cases of operational model codes. We propose a non-intrusive reduced order scheme, and study its application to a full chain of operational models. Reduced basis are constructed using principal component analysis (PCA), and the concentration fields are approximated as projections onto this reduced space. We use statistical emulation to approximate projection coefficients in a non-intrusive manner. We apply a multi-level meta-modeling technique to a chain using the dynamic traffic assignment model LADTA, the emissions database COPERT IV, and the urban dispersion-reaction air quality model SIRANE to a case study on the city of Clermont-Ferrand with over 45, 000 daily traffic observations, a 47, 000-link road network, a simulation domain covering $$180\,\text {km}^2$$ 180 km 2 . We assess the results using hourly NO$$_2$$ 2 concentration observations measured at stations in the agglomeration. Computational times are reduced from nearly 3 h per simulation to under 0.1 s, while maintaining accuracy comparable to the original models. The low cost of the meta-model chain and its non-intrusive character demonstrate the versatility of the method, and the utility for long-term or many-query air quality studies such as epidemiological inquiry or uncertainty quantification.

Sign in / Sign up

Export Citation Format

Share Document