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The Impact of Traffic-Related Pollutant on Indoor Air Quality in Buildings Near Main Roads

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The Impact of Traffic-Related Pollutant on Indoor Air Quality in Buildings Near Main Roads Proceedings: Building Simulation 2007 THE IMPACT OF TRAFFIC-RELATED POLLUTANT ON INDOOR AIR QUALITY IN BUILDINGS NEAR MAIN ROADS Jing Liu, Jianing Zhao, Dexing Sun School of Municipal & Environmental Engineering, Harbin Institute of Technology Harbin 150090, China some cancers have all been linked to traffic ABSTRACT emissions (Kousa A. et al. 2002, Colvile R.N. et al. Traffic–related pollutant has been recognized as an 2003). air pollution hot spot due to its large emission rate To keep good indoor air quality, ventilation system and great health impacts for the exposed population. for buildings in urban environment should maintain In the present investigation, a computational fluid required ventilation rate to remove and dilute indoor dynamics technique is used to evaluate the effect of pollutant, and avoid the adverse effect of outdoor traffic pollutions on indoor air quality of a naturally pollutant at the same time. Ekberg (1996) and Green ventilated building. The transport of street-level et al. (1998) respectively carried out academic nonreactive pollutants emitted from motor vehicles attempts regarding control strategies for reducing the into the indoor environment is simulated using the impact of outdoor traffic pollutants on indoor air RNG k-ε model of the turbulent flows and the quality of a building next to busy roads. However, pollutant transport equations. Three typical they assumed that all the air entering the room had configurations of street canyons and six ventilation same pollutant concentration. This assumption scenarios are considered. It is found that the layout of ignored the spatial variations in the concentrations of street canyon affects not only the airflow pattern but pollutant around buildings. Green et al. (2001) also the ventilation rates, paths and indoor air quality conducted wind-tunnel and full-scale measurement to for that building. When the studied building is examine CO levels around a building located in close located in the street canyon with aspect rate 0.2, to busy roads. It was concluded that indoor pollutant using the leeward cross-flow ventilation with concentration could be reduced when air intakes windward upper vent can effectively lower incoming were located in the regions of low concentration of vehicle pollutants and maintain a desirable air change traffic pollution. T. J. Chang (2002) investigated the rate during traffic rush hours. But when the street effect of traffic pollution on indoor air quality of a canyon aspect rate is equal to 0.5, this ventilation naturally ventilated building using CFD technology. mode has no significant advantage compared with He claimed that reasonable ventilation design could other cross ventilation modes. Moreover, the leeward effectively lower incoming vehicle pollutants and side vents may become a significant factor maintain a desirable air change rate during traffic contributing to indoor concentration of traffic rush hours, and recommended that the ventilation pollutants when the studied buildings are located in a mode using the leeward cross-flow ventilation with narrow street such as aspect rate equal to 1. the windward roof vent was the most effective one for buildings near main road. Major limitation of this KEYWORDS study is to consider only a single building case, Street canyon, Traffic pollutants, Natural ventilation, which may have great difference from real urban Indoor air quality, RNG environment. The main objective of this research is to investigate INTRODUCTION the transmission of outdoor air contaminant into Traffic pollution is of increasing concern in many of buildings and find optimum ventilation strategies for the world's cities. With the growth in road traffic, the naturally ventilated buildings located in street canyon motor vehicle exhaust has become the most environment, which suffer high concentration of predominant source of air pollution in the urban outdoor pollutant. In this paper, the street canyon centers over the world, despite significant effect was considered, and both ventilation rate and improvements in fuel and engine technology. It indoor air quality were investigated in every street typically accounts for 80% of CO emissions, 25% of canyon configuration and ventilation mode. The fine particulate emissions, 40-50% of VOC appropriate control strategies for lowering incoming emissions and 90% of benzene emissions in many vehicle pollutants and maintaining an acceptable air countries, and even higher proportions in some urban change rate are examined to reduce the impact of areas (Simon Kingham et al. 2003). Although the outdoor traffic pollutants on indoor air quality. health effects of these pollutants are not yet fully understood, asthma, other respiratory diseases and - 862 - Proceedings: Building Simulation 2007 NUMERICAL SIMULATIONS ′ ′ is the Reynolds stress; 2 , is −uuij μt = ρεCkμ / μt Model description the turbulent viscosity; μ is the molecular viscosity; is the turbulent kinetic energy RNG k-ε model is applied in the present paper, Gk because this model is more precious than standard k- production; αk and αε are the inverse effective ε model and needs less computational source than Prandtl number for k and ε respectively; μ is the LES when investigating air flow around buildings (G. eff Evola and V. Popov. 2006). effective turbulent viscosity;η = Sk /ε ; S is the scalar measure of the deformation tensor; the constants of The air around buildings can be regarded as an η and β are 4.38 and 0.012, respectively; Ci is the incompressible turbulent inert flow, and the air and 0 pollutant densities are assumed to be constant. These chemical species (pollutants) concentration; Di is the assumptions are reasonable for most lower diffusivity; Sct is the turbulent Schmidt number. All atmosphere environments as described by Sini et the above calculations were performed using the al.(1996). Besides, the turbulence production due to FLUENT code. the buoyancy effect is not taken into consideration in the present study. Computational domain and boundary conditions The equations of mass, momentum are written in A two dimensional computational domain is used Cartesian tensor notation as follows (T.L. Chan et al. with wind direction assumed to be perpendicular to 2002): the street canyon. The downstream building (B2) is chosen as the studied building. There are two vents Continuity equation: on the windward side and leeward sides of B2 ∂ui respectively, and the height of each vent is 1.5m. = 0 (1) ∂x Fig.1 shows the computational street canyon i configuration and the opens’ location on B2, where Momentum equation: W is the street width and H is the building height. 2 ∂∂uu∂()uuji 1 ∂p μ The vehicular emissions are considered as a line ii+=−+ ∂∂txρρ ∂ x ∂∂ xx source located at the center of the street. CO is used jijj as a representative automotive emission gas because ∂ it is relatively stable, easily measured and comes − ()uu′′ (2) ∂x ij mainly from vehicle emissions. Initial concentration j of emissions is presented in dimensionless form 1. k and ε transport equations in RNG k-ε turbulence model: At the inflow boundary, the inflow vertical wind ()ku ⎡ ⎤ speed profile is assumed to be in a power- law form ∂∂∂kk∂ j 1 as follows: +=⎢αμkeff ⎥ ∂∂txjjρ ∂ x⎢ ∂ x j⎥ ⎣ ⎦ z 0.299 UUir= () (6) Gk +−ε (3) zr ρ Where zr and Ur are specified as 10m (the height of -1 ∂∂∂ε ∂()ku j 11⎡⎤εεbuildings) and 0.5ms , respectively. The inflow +=⎢⎥αμεεekff +CG 1 ∂∂txρρ ∂ x ∂ x kturbulent kinetic energy profile is presented by jj⎣⎦ j 2 3 2 kaUii= (7) ⎡⎤Cμ ρη(1− η / η0 ε −+C (4) ⎢⎥ε 2 3 Where a is a parameter that controls the inflow ⎣⎦⎢⎥1+ βη k turbulence intensity and specified as 0.005. And the inflow dissipation rate profile is given by The species (pollutants) transport equation: 3/4 3/2 ∂∂CC1 ∂ ⎡⎛⎞μ ∂ C⎤ Ckμ i ii ti (8) +=uD⎢ + ⎥ (5) ε i = ji⎜⎟ kz ∂∂txxjjρ ∂⎣⎢⎝⎠ Scx tj ∂⎦⎥ Where Where Cμ is a constant (=0.09) and k is the von ∂u 12∂ui j Karman constant (=0.4). −=uuij′′ μ t() + − kδ ij ρ ∂∂xxji3 - 863 - Proceedings: Building Simulation 2007 Figure 1 Sketch of the calculation domain The measured pollutant concentrations in the wind- tunnel were expressed in the dimensionless pollutant No-slip velocity boundary conditions are applied to concentration form K, which is defined as: all solid surfaces and the ground, and symmetric boundary is used at upper boundary. At the outlet of CU HL K = ref (9) the computational domain, a constant pressure is Q assumed. The initial conditions of both the velocity and concentration fields are set to zero in the entire Where C is the volume fraction of contaminant; H is computational domain. A structured grid system with the height of building; L is the length of line source; 350 grids in the horizontal and 160 grids in the Q is the volume flow rate of contaminant. vertical is used. Finer grids are located close to the Fig. 2 shows the dimensionless pollutant building and ground and then expand further away. concentration (K) distributions on the leeward side The expansion ratio in this non-uniform grid system and windward side of the street canyon when the is 1.1. Extensive tests of the independence of the ratio H/W=1. The simulation results present good meshes are carried out with increasing mesh number agreement with the measured data in wind tunnel, but until further refinement is shown to be less under-predict the dimensionless concentrations on significant. The second order linear upwind the leeward side of the street canyon, especially at difference scheme has been used to avoid the errors the lower part. In spite of the difference, both produced by numerical diffusion when using the first profiles are similar to each other suggesting the order upwind scheme. numerical model can be used for simulating airflow Model validation and pollutant dispersion in an urban street canyon.
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