Street-in-Grid modeling of gas-phase pollutants in Paris city

Abstract

<p><strong>Abstract.</strong> Regional-scale chemistry-transport models have coarse spatial resolution, and thus can only simulate background concentrations. They fail to simulate the high concentrations observed close to roads and in streets, i.e. where a large part of the urban population lives. Local-scale models may be used to simulate concentrations in streets. They often assume that background concentrations are constant and/or use simplified chemistry. Recently developed, the multi-scale model Street-in-Grid (SinG) estimates gaseous pollutant concentrations simultaneously at local and regional scales, coupling them dynamically. This coupling combines the regional-scale chemistry-transport model Polair3D and the street network model MUNICH (Model of Urban Network of Intersecting Canyons and Highway). MUNICH models explicitly street canyons and intersections, and it is coupled to the first vertical level of the chemical-transport model, enabling the transfer of pollutant mass between the street canyon roof and the atmosphere. The original versions of SinG and MUNICH adopt a stationary hypothesis to estimate pollutant concentrations in streets. Although the computation of NO<sub><i>x</i></sub> concentration is numerically stable with the stationary approach, the partitioning between NO and NO<sub>2</sub> is highly dependent on the time step of coupling between transport and chemistry processes. In this study, a new non-stationary approach is presented with a fine coupling between transport and chemistry, leading to numerically stable partitioning between NO and NO<sub>2</sub>. Simulations of NO, NO<sub>2</sub> and NO<sub><i>x</i></sub> concentrations over Paris city with SinG, MUNICH and Polair3D are compared to observations at traffic and urban stations to estimate the added value of multi-scale modeling with a dynamical coupling between the regional and local scales. As expected, the regional chemical-transport model underestimates NO and NO<sub>2</sub> concentrations in the streets. However, there is a good agreement between the measurements and the concentrations simulated with MUNICH and SinG. The dynamic coupling between the local and regional scales tends to be important for streets with an intermediate aspect ratio and with high traffic emissions.</p>

Street-scale air quality modelling for Beijing during a winter 2016 measurement campaign

“…This is a result of the fast reaction of O 3 with NO (titration) (Reaction R4) which dominates in high-NO x environments (Y. Tang et al, 2017;Ma et al, 2018), such as those next to major roads. The conversion of primary NO exhaust emissions to NO 2 , following the titration of O 3 , also produces a sharply increasing NO 2 /NO x ratio with distance from the road centre (Fig.…”

Author's response to referee comments

“…Land use regression (LUR) modelling studies, combining geospatial indicators with air quality measurement data, can generate local scale (<1 km) pollutant level variations, but have been limited by the sparsity of monitoring network data available in Beijing (J. . Alternatively, box models, such as The Model of Urban Network of Intersecting Canyons and Highways (MUNICH), are used to calculate pollutant concentrations within street canyons, but require detailed information on the spatial dimensions of a city's street canyons and are restricted by assumptions of uniform concentrations along individual road segments (Lugon et al 2019). "…”

“…As described in detail in response to reviewer comment 3, on Page 3 Line 86 and 89 recent studies describing alternative urban air quality modelling techniques are added -J. , M. and Lugon et al (2019). Page 2/3 Line 84-89 now reads:…”