Hello!

I would start with inMAP:

Global, High-Resolution, Reduced-Complexity Air Quality Modeling Using InMAP(Intervention Model for Air Pollution)

https://chemrxiv.org/engage/chemrxiv/article-details/60c756c90f50dbc115398148

Here the GitHub https://github.com/spatialmodel/inmap

I have never tried it but I would like to. You need to input shapefiles with annual emissions. It is fast, but you still need an annual WRF run for meteorology.

In UK, you could try with NAME:

https://www.metoffice.gov.uk/research/approach/modelling-systems/dispersion-model

For specific street emissions, you have:

• Model of Urban Network of Intersecting Canyons and Highways (MUNICH) https://www.geosci-model-dev.net/11/611/2018/
• R-LINE (CMAS): https://www.cmascenter.org/r-line/
• Stochastic Time-Inverted Lagrangian Transport model (STILT-R version 2) https://www.geosci-model-dev.net/11/2813/2018/

I had a similar question here https://www.researchgate.net/post/Which_models_do_you_know_for_pollutants_dispersion_of_line_street_sources

Additional:

To estimate emissions I would recommend my model VEIN (Article VEIN v0.2.2: an R package for bottom–up vehicular emissions ...

And to convert the emissions into inputs for air quality model, I would suggest my model EIXPORT (Article eixport: An R package to export emissions to atmospheric models

https://github.com/atmoschem/eixport

Hi,

If you are looking for dispersion models which simulate the transportation and dispersion of emissions from limited number of emission points, I would recommend you try HYSPLIT. HYSPLIT is one the most used atmospheric dispersion models in the world, and it is open. The model can be run online or in batch mode, for either forward or backward simulations.

Here is the link to HYSPLIT:

https://www.ready.noaa.gov/HYSPLIT.php

Jian

Hi,

One dispersion model widely used is AERMOD. It is a preferred and recommended model of the US EPA:

https://www.epa.gov/scram/air-quality-dispersion-modeling-preferred-and-recommended-models#aermod

Thank you everyone. I will update this answer soon too with results from my own search, which included some other options.

Sergio Ibarra-Espinosa, do you know much about NAME and whether it is appropriate for city-scale emissions and air quality changes? Do you know what is it finest spatial resolution? I can see a lot of applications with it for volcanic eruptions, chemical and nuclear incidents but not with transportation policies for example resulting in vehicle emission changes? I am interested in transportation policies.

Thanks everyone. Your answers will also be useful to me.

Haneen Khreis Yeah, I know what you mean.

I have never tried NAME but it looks fun. It can read line sources, which seems fine to obtain the dispersion of emissions from streets. So, in order to asses the impact you would first need a complete emissions inventory of all sources including your own vehicular emissions, model the dispersion, and then iterate with different vehicular emissions scenarios. I believe that 1 year simulations is appropriate, but you can asses shorter periods of time as well (as I show on my explanation below using WRF-Chem.

Another interesting model is CityChem: https://www.researchgate.net/project/CityChem-City-scale-Chemistry-Transport-Model I tried to test it last year, but I could not finish my test because I have so much obligations estimating vehicular emissions for Sao Paulo. CityChem does not have limitation of number of sources and it is designed to be used at city scale.

I would recommend you to try with models which cover all type of sources with hourly resolution, such as NAME or CityChem, but I don't know if NAME can be used in a complex city such as London.

Anyways, if you need help, let me know, I would be super happy to collaborate.

I have used WRF-Chem to test different transportation policies in São Paulo. We studied the impact of different emissions standards, future scenarios and mobility configurations (more bus usage, more electric cars and so on) on air quality, as seen on the attached figures. We do that by selecting period of study to estimate emissions, then model air quality with wrf chem and then we repeat he process with different set of emissions. The resolution depend on the computation power, with a sub-km scale possible. However, the model solves a numerical grid and not lines. Here a paper using WRFChem (in portuguese) Research QUALAMET: Modelagem do Impacto das Emissões Veiculares com d...

Jian Feng, have you ever used HYSPLIT? Can you comment on what scale it is appropriate for and what spatial resolution the outcomes can be produced at?

I have been using HYSPLIT as well as our Canadian dispersion models. HYSPLIT is a Lagrangian particle model. The spatial resolution of the numerical weather prediction (NWP) models used by HYSPLIT is around 10 km ( to be confirmed). In terms of the spatial resolution of a Lagrangian dispersion model, I think it depends on the time step as well the number of particles used. In my experience, we can have a spatial resolution fine enough for an urban scale as well as a coarse resolution for an application of global scale using Canadian dispersion models. However, for HYSPLIT, the minimum time step is 1 minute. Based on https://www.ready.noaa.gov/hypub/limitations.html, for scales less than 1 km, the CAMEO/ALOHA model is recommended.

Thank you, all. Here is what I found so far from my search, which is still ongoing:

• Gilmore et al. 2019. An inter-comparison of the social costs of air quality from reduced-complexity models. Environmental Research Letters, 14(7), p.074016.
• Tessum et al. 2017. InMAP: A model for air pollution interventions. PloS one, 12(4), p.e0176131.
• Thakrar S, Tessum C, Apte J, Balasubramanian S, Millet DB, Pandis S, et al. Global, High-Resolution, Reduced-Complexity Air Quality Modeling Using InMAP(Intervention Model for Air Pollution). ChemRxiv. Cambridge: Cambridge Open Engage; 2021; This content is a preprint and has not been peer-reviewed.
• Heo, J. et al. (2016). Reduced form modeling of public health impacts of inorganic PM2.5 and precursor emissions. Atmospheric Environment, 137, pp.80-89.
• European Commission Joint Research Center, FAst Scenario Screening Tool: https://tm5-fasst.jrc.ec.europa.eu/
• Van Dingenen et al. 2018. TM5-FASST: a global atmospheric source–receptor model for rapid impact analysis of emission changes on air quality and short-lived climate pollutants. Atmospheric Chemistry and Physics, 18(21), pp.16173-16211.
• SHERPA: a computational model for better air quality in urban areas: https://ec.europa.eu/jrc/en/news/sherpa-computational-model-better-air-quality-urban-areas.
• Thunis, P., Degraeuwe, B., Pisoni, E., Trombetti, M., Peduzzi, E., Belis, C.A., Wilson, J., Clappier, A. and Vignati, E., 2018. PM2. 5 source allocation in European cities: A SHERPA modelling study. Atmospheric Environment, 187, pp.93-106.
• Degraeuwe, B., Pisoni, E., Christidis, P., Christodoulou, A. and Thunis, P., 2021. SHERPA-city: A web application to assess the impact of traffic measures on NO2 pollution in cities. Environmental Modelling & Software, 135, p.104904.
• The Long-range Energy Alternatives Planning – Integrated Benefits Calculator (LEAP-IBC), by the Stockholm Environment Institute, https://www.sei.org/publications/leap-ibc/
• Kuylenstierna, J.C., Heaps, C.G., Ahmed, T., Vallack, H.W., Hicks, W.K., Ashmore, M.R., Malley, C.S., Wang, G., Lefevre, E.N., Anenberg, S.C. and Lacey, F., 2020. Development of the Low Emissions Analysis Platform–Integrated Benefits Calculator (LEAP-IBC) tool to assess air quality and climate co-benefits: Application for Bangladesh. Environment International, 145, p.106155.
• The United Kingdom Met Office's Numerical Atmospheric-dispersion Modelling Environment (NAME): https://www.metoffice.gov.uk/research/approach/modelling-systems/dispersion-model
• Kim, Y., Wu, Y., Seigneur, C. and Roustan, Y., 2018. Multi-scale modeling of urban air pollution: development and application of a Street-in-Grid model (v1. 0) by coupling MUNICH (v1. 0) and Polair3D (v1. 8.1). Geoscientific Model Development, 11(2), pp.611-629.
• Karl, M., 2018. Development of the city-scale chemistry transport model citychem-episode and its application to the city of hamburg. Geoscientific Model Development Discussions, pp.1-60.

Most of these are "reduced-form or reduced-complexity" and some are not.

The answers to this question also interest me

Hi Haneen, sorry to be late to the party, but could SHERPA be the one "tool to rule them all"?

https://aqm.jrc.ec.europa.eu/sherpa.aspx

Best wishes,

Christian

Thanks Christian Brand

Yes, I have been looking at it and will probably use it too.

Here is a document for everyone summarizing all the options that I found. Hope this is helpful.

The pionner open source Screen 3 of the EPA

https://www.epa.gov/scram/air-quality-dispersion-modeling-screening-models

ADMS4 is in my opinion one of the best gaussian models for atmospheric dispersion

The pionner open source Screen 3 of the EPA

https://www.epa.gov/scram/air-quality-dispersion-modeling-screening-models

ADMS4 is in my opinion one of the best gaussian models for atmospheric dispersion