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HERMESv3, a stand-alone multi-scale atmospheric emission modelling framework – Part 2: The bottom–up module
We describe the bottom–up module of the High-Elective Resolution Modelling Emission System version 3 (HERMESv3), a Python-based and multi-scale modelling tool intended for the processing and computation of atmospheric emissions for air quality modelling. HERMESv3 is composed of two separate modules:...
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Published in: | Geoscientific Model Development 2020-03, Vol.13 (3), p.873-903 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | We describe the bottom–up module of the High-Elective
Resolution Modelling Emission System version 3 (HERMESv3), a Python-based
and multi-scale modelling tool intended for the processing and computation of
atmospheric emissions for air quality modelling. HERMESv3 is composed of two
separate modules: the global_regional module and the bottom_up module. In a companion paper (Part 1,
Guevara et al., 2019a) we presented the global_regional module. The bottom_up module described in
this contribution is an emission model that estimates anthropogenic
emissions at high spatial- (e.g. road link level,) and temporal- (hourly)
resolution using state-of-the-art calculation methods that combine local
activity and emission factors along with meteorological data. The model
computes bottom–up emissions from point sources, road transport, residential
and commercial combustion, other mobile sources, and agricultural activities.
The computed pollutants include the main criteria pollutants (i.e. NOx, CO,
NMVOCs (non-methane volatile organic compounds), SOx, NH3, PM10 and PM2.5) and greenhouse gases
(i.e. CO2 and CH4, only related to combustion processes). Specific
emission estimation methodologies are provided for each source and are
mostly based on (but not limited to) the calculation methodologies reported
by the European EMEP/EEA air pollutant emission inventory guidebook.
Meteorologically dependent functions are also included to take into account
the dynamical component of the emission processes. The model also provides
several functionalities for automatically manipulating and performing
spatial operations on georeferenced objects (shapefiles and raster files).
The model is designed so that it can be applicable to any European
country or region where the required input data are available. As in the case of
the global_regional module, emissions can be estimated on several user-defined grids,
mapped to multiple chemical mechanisms and adapted to the input requirements
of different atmospheric chemistry models (CMAQ, WRF-Chem and MONARCH) as
well as a street-level dispersion model (R-LINE). Specific emission outputs
generated by the model are presented and discussed to illustrate its
capabilities. |
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ISSN: | 1991-9603 1991-959X 1991-962X 1991-9603 1991-962X |
DOI: | 10.5194/gmd-13-873-2020 |