Urban Main Roads Research Articles

Roadside Air Quality Simulation Model for Urban Main Roads in Japan Clean Air Program (II)

Roadside Air Quality Simulation Model for Urban Main Roads in Japan Clean Air Program (II)

Numerical Simulation Model for Predicting Air Quality along Urban Main Roads. 2nd Report Development of Photochemical Reaction Model.

A simulation model for predicting air quality along urban main roads is being studied. The previous report dealt with the development of atmospheric diffusion model, which will be the platform of the entire simulation model. The present report describes the development of a photochemical reaction model, which will be incorporated into the overall simulation program. Focusing on nitrogenoxides, a simplifed 4-component, 5-reaction model has been established. The validity of the model was verified by comparison with data obtained in a chamber experiment. More compelx models containing up to 30-component, 67-reaction have also been constructed to conduct performance comparisons with the simplified model. The difference in the calculated results among the models was found to be less than 1%. The simplified model was applied to a street canyon condition, and the reaction occurring there was visualized.

Numerical simulation model for predicting air quality along urban main roads: First report, development of atmospheric diffusion model

A simulation model for predicting air quality along urban main roads is being studied. The objective of the model is to predict the effects on air quality of various road-related parameters such as configurations of roads and surrounding buildings as well as traffic flow, chemical reactions, and other related phenomena. In this paper, the development of an atmospheric diffusion model, which will be the platform of the whole simulation model, is reported. A new concentration diffusion coefficient model is proposed, in which the effect of vehicle wind is taken into account. By comparing with field experiments in which the diffusing tracer gas concentration was measured in a real street canyon, the validity of the simulation model is verified. Also, the new diffusion coefficient model is found to be capable of improving predictive accuracy of air quality around a street canyon. © 1998 Scripta Technica, Heat Trans Jpn Res, 27(7): 483–496, 1998

Numerical Simulation Model for Predicting Air Quality along Urban Main Roads. 3rd Report. Incorporation of Traffic Flow Model.

A simulation model for predicting air quality along urban main roads is being studied. The previous reports dealt with the development of atmospheric diffusion model and a photochemical reaction model as well as traffic flow model. The present report describes the incorporation of the atmospheric diffusion model and the traffic flow model, which enables simulation of the effect of traffic parameters on air quality along the main roads. Emission mass from each vehicle is calculated by the traffic flow model using instanteneous velocity and accelaration of the vechiles. Then, the emission data is converted into increase of concentration, and passed into the atmospheric diffusion model for its source term. A case study was conducted using the incorporated model, in which some traffic parameters were studied to show their infulence on traffic flow and air qulity around the road.

Numerical simulation model for predicting air quality along urban main roads: First report, development of atmospheric diffusion model

A simulation model for predicting air quality along urban main roads is being studied. The objective of the model is to predict the effects on air quality of various road-related parameters such as configurations of roads and surrounding buildings as well as traffic flow, chemical reactions, and other related phenomena. In this paper, the development of an atmospheric diffusion model, which will be the platform of the whole simulation model, is reported. A new concentration diffusion coefficient model is proposed, in which the effect of vehicle wind is taken into account. By comparing with field experiments in which the diffusing tracer gas concentration was measured in a real street canyon, the validity of the simulation model is verified. Also, the new diffusion coefficient model is found to be capable of improving predictive accuracy of air quality around a street canyon. © 1998 Scripta Technica, Heat Trans Jpn Res, 27(7): 483–496, 1998

都市内幹線道路沿線における大気質予測シミュレーションシステムの構築

A simulation model for predicting air quality along urban main roads is being studied. The objective of the model is to predict the effects on air quality of various road-related parameters such as configurations of roads and surrounding buildings as well as traffic flow, chemical reaction, and other related phenomena. In this paper, the development of an atmospheric diffusion model, which will be the platform of the whole simulation model, is reported. A new concentration diffusion coefficient model is proposed, in which the effect of vehicle wind is taken into account. By comparing with field experiments in which the diffusing tracer gas concentration was measured in a real street canyon, the validity of the simulation model is verified. Also the new diffusion coefficient model is found to be capable of improving predictive accuracy of air quality around the street canyon.

Traffic noise measurements on urban main roads with gradients

Measurements of road traffic noise were made at 18 locations on single-carriageway hilly main roads, subjected to speed limits, in the Greater London area. The observation sites were 10 m from the kerbside and in positions where the flow of vehicles was relatively steady. Variations of L 10 , L 50 and L 90 with rates of flow of heavy and light vehicles, and also with gradients, were determined. The changes of the sound levels with vehicle flow followed a predicted pattern. Because of the relatively high degree of scatter obtained in determining mean values of L 10 , L 50 and L 90 under given conditions, for a particular gradient, no definite relation could be established between sound levels and gradient.