scholarly journals Analysis of particulate matter concentration and size distribution in heavy-duty vehicle exhaust emissions

2001 ◽  
Author(s):  
Zhuyun Xu
Keyword(s):  
Particulate Matter ◽  
Size Distribution ◽  
Exhaust Emissions ◽  
Heavy Duty ◽  
Vehicle Exhaust ◽  
Particulate Matter Concentration ◽  
Heavy Duty Vehicle ◽  
Matter Concentration

scholarly journals An Urban Lagrangian Stochastic Dispersion Model for Simulating Traffic Particulate-Matter Concentration Fields

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 580
Author(s):  
Eyal Fattal ◽  
Hadas David-Saroussi ◽  
Ziv Klausner ◽  
Omri Buchman
Keyword(s):  
Surface Layer ◽  
Particulate Matter ◽  
Urban Area ◽  
Hybrid Approach ◽  
Urban Morphology ◽  
Dispersion Pattern ◽  
Vertical Column ◽  
Particulate Matter Concentration ◽  
Vertical Heterogeneity ◽  
Matter Concentration

The accumulated particulate matter concentration at a given vertical column due to traffic sources in urban area has many important consequences. This task, however, imposes a major challenge, since the problem of realistic pollutant dispersion in an urban environment is a very demanding task, both theoretically and computationally. This is mainly due to the highly inhomogeneous three dimensional turbulent flow regime in the urban canopy roughness sublayer, which is far from “local equilibrium” between shear production and dissipation. We present here a mass-consistent urban Lagrangian stochastic model for pollutants dispersion, where the flow field is modeled using a hybrid approach by which we model the surface layer based on the typical turbulent scales, both of the canopy and in the surface layer inertial sub-layer. In particular it relies on representing the canopy aerodynamically as a porous medium by spatial averaging the equations of motion, with the assumption that the canopy is laterally uniform on a scale much larger than the buildings but smaller than the urban block/neighbourhood, i.e., at the sub-urban-block scale. Choosing the spatial representative averaging volume allows the averaged variables to reflect the characteristic vertical heterogeneity of the canopy but to smooth out smaller scale spatial fluctuations caused as air flows in between the buildings. This modeling approach serves as the base for a realistic and efficient methodology for the calculation of the accumulated concentration from multiple traffic sources for any vertical column in the urban area. The existence of multiple traffic sources impose further difficulty since the computational effort required is very demanding for practical uses. Therefore, footprint analysis screening was introduced to identify the relevant part of the urban area which contributes to the chosen column. All the traffic sources in this footprint area where merged into several areal sources, further used for the evaluation of the concentration profile. This methodology was implemented for four cases in the Tel Aviv metropolitan area based on several selected summer climatological scenarios. We present different typical behaviors, demonstrating combination of source structure, urban morphology, flow characteristics, and the resultant dispersion pattern in each case.

scholarly journals Impact of COVID-19 lockdown on the fine particulate matter concentration levels: Results from Bengaluru megacity, India

2021 ◽  
Vol 67 (7) ◽  
pp. 2140-2150
Author(s):  
V. Sreekanth ◽  
Meenakshi Kushwaha ◽  
Padmavati Kulkarni ◽  
Adithi R. Upadhya ◽  
B. Spandana ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Fine Particulate Matter ◽  
Particulate Matter Concentration ◽  
Fine Particulate ◽  
Matter Concentration ◽  
Concentration Levels

scholarly journals Fine particulate matter concentration and composition and the incidence of childhood asthma

2021 ◽  
Vol 152 ◽  
pp. 106486
Author(s):  
Éric Lavigne ◽  
Robert Talarico ◽  
Aaron van Donkelaar ◽  
Randall V. Martin ◽  
David M. Stieb ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Childhood Asthma ◽  
Fine Particulate Matter ◽  
Particulate Matter Concentration ◽  
Fine Particulate ◽  
Matter Concentration
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