Abstract
Abstract. Regional-scale chemistry-transport models have coarse spatial resolution (coarser than 1 km ×1 km) and can thus only simulate background concentrations. They fail to simulate the high concentrations observed close to roads and in streets, 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 by coupling them dynamically. This coupling combines the regional-scale chemistry-transport model Polair3D and a street-network model, the Model of Urban Network of Intersecting Canyons and Highway (MUNICH), with a two-way feedback. MUNICH explicitly models 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 the NOx concentration is numerically stable with the stationary approach, the partitioning between NO and NO2 is highly dependent on the time step of coupling between transport and chemistry processes. In this study, a new nonstationary approach is presented with a fine coupling between transport and chemistry, leading to numerically stable partitioning between NO and NO2. Simulations of NO, NO2 and NOx concentrations over Paris 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 two-way dynamical coupling between the regional and local scales. As expected, the regional chemical-transport model underestimates NO and NO2 concentrations in the streets. However, there is good agreement between the measurements and the concentrations simulated with MUNICH and SinG. The two-way dynamic coupling between the local and regional scales tends to be important for streets with an intermediate aspect ratio and with high traffic emissions.
Highlights
Air pollution is a serious problem in many cities due to its considerable impacts on human health and the environment, as reported in WHO (2006), Brønnum-Hansen et al (2018), Lee et al (2018), Chen et al (2019), Katoto et al (2019), and De Marco et al (2019)
Lugon et al.: Nonstationary modeling of NO2, NO and NOx in Paris using the Street-in-Grid model are available in the literature: e.g., Polair3D, Weather Research and Forecasting (WRF)-Chem, CHIMERE, the Community Multi-scale Air Quality Modeling System (CMAQ) and the Air Quality Model For Urban Regions Using An Optimal Resolution Approach (AURORA) are described in Sartelet et al (2007), Zhang et al (2010), Menut et al (2014), Byun and Ching (1999), and Mensink et al (2001), respectively
Pollutant concentrations are calculated in streets at the local scale, and they are transferred to the regional scale with a vertical mass flux between the street and the regional background concentrations of the first vertical grid level of the chemistry-transport models (CTMs)
Summary
Air pollution is a serious problem in many cities due to its considerable impacts on human health and the environment, as reported in WHO (2006), Brønnum-Hansen et al (2018), Lee et al (2018), Chen et al (2019), Katoto et al (2019), and De Marco et al (2019). The Model of Urban Network of Intersecting Canyons and Highways (MUNICH), developed by Kim et al (2018), presents a similar box-model parameterization as SIRANE, but it does not employ a Gaussian model to determine background concentrations They may be provided by measurements, as in Kim et al (2018), or regional-scale CTMs, as in our study. Comparisons between the annual average concentrations calculated with THOR and measured at air-quality stations show fairly good agreement, especially for NO2, whereas PM2.5 and PM10 are underestimated With this kind of one-way multi-scale modeling, traffic emissions are counted twice: they are input to the street model to estimate street concentrations and to the regional model to estimate background concentrations. The sixth section studies the influence of the two-way dynamic coupling between the regional and local scales
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