the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Modelling concentration heterogeneities in streets using the street-network model MUNICH
Alice Maison
Yelva Roustan
Matthias Ketzel
Steen Solvang Jensen
Youngseob Kim
Christophe Chaillou
Abstract. Populations in urban areas are exposed to high local concentrations of pollutants, such as nitrogen dioxide and particulate matter, because of unfavorable dispersion conditions and the proximity to traffic. To simulate these concentrations over cities, models like the street-network model MUNICH (Model of Urban Network of Intersecting Canyons and Highways) rely on parameterizations to represent the air flow and the concentrations of pollutants in streets. In the current version MUNICH v2.0, concentrations are assumed to be homogeneous in each street segment. A new version of MUNICH where the street volume is discretized is developed to represent the street gradients and better estimate people exposure. Three vertical levels are defined in each street segment. A horizontal discretization is also introduced under specific conditions by considering two zones with a parameterization taken from the Operational Street Pollution Model (OSPM). Simulations are performed over two districts of Copenhagen, Denmark, and one district of Greater Paris, France. Results show an improvement of the comparison to observations with higher concentrations at the bottom of the street, closer to traffic, of pollutants emitted by traffic (NOx, black carbon, organic matter). Finally, a sensitivity analysis to the influence of the street network highlights the importance to use the model MUNICH with a network rather than with a single street.
Thibaud Sarica et al.
Status: open (until 12 Jun 2023)
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RC1: 'Comment on gmd-2023-70', Anonymous Referee #1, 08 May 2023
reply
Distribution of air pollution in street canyon environments are highly heterogeneous. Homogenous assumption may be inappropriate to capture large concentration gradient in the streets, especially in narrower streets. An advanced version of the street-network model MUNICH (Model of Urban Network of Intersecting Canyons and Highways) was developed in this paper to achieve the representation of concentration gradients in streets. The model was then applied to real streets. Simulated results were compared with observations and other models, i.e. Operational Street Pollution Model (OSPM) and homogenous version of MUNICH, showing the advantages of the advanced MUNICH. A sensitivity test with and without street network shows the need to use a street network (rather than a single street) in the MUNICH. There are some comments as follows:
- Line 70: Apart from the chemical transformation, were the aerosol processes as mentioned in Lines 43-44 also considered for PM in this study?
- Line 117: Why 3 vertical levels? Can it be increased to capture more vertical variation if needed?
- Line 181: Were the simulations conducted in every hour over the year?
- Lines 192-195: please provide readers with a bit more details about WRF, UBM and OML-Highway model.
- Line 204-206: what are the values for H and W? Please provide more details about how the street parameters are derived for the street network (as indicated in Fig.4)?
- Line 215-216: The underestimation for NO2 may be also attributed to the missing of VOC chemistry.
- Line 221: OSPM can capture the difference horizonal heterogeneities in the street (as mentioned in Line 212), while MUNICH-hete-11 can only represent the average in the whole of first vertical layer. How can it be considered as improvement for MUNICH in this aspect?
- Line 268: Are PM2.5 and PM10 considered as passive tracers, or with aerosol processes?
- Fig. 7: units were not shown clearly.
- Line 314: Please add discussion about the influence of aspect ratio (AR). Which AR is favourable for the MUNICH-hete?
- Line 331: Also to include VOC chemistry for the next step?
Citation: https://doi.org/10.5194/gmd-2023-70-RC1 -
RC2: 'Referee Comment on gmd-2023-70', Anonymous Referee #2, 13 May 2023
reply
My reviewer comments on gmd-2023-70 are in the attached Supplement.
Thibaud Sarica et al.
Thibaud Sarica et al.
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