Top–down quantification of NO<sub><i>x</i></sub> emissions from traffic in an urban area using a high-resolution regional atmospheric chemistry model
With NO<sub>2</sub> limit values being frequently exceeded in European cities, complying with the European air quality regulations still poses a problem for many cities. Traffic is typically a major source of NO<sub><i>x</i></sub> emissions in urban areas. High...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2018-06-01
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| Series: | Atmospheric Chemistry and Physics |
| Online Access: | https://www.atmos-chem-phys.net/18/8203/2018/acp-18-8203-2018.pdf |
| _version_ | 1811215090958991360 |
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| author | F. Kuik F. Kuik A. Kerschbaumer A. Lauer A. Lupascu E. von Schneidemesser T. M. Butler T. M. Butler |
| author_facet | F. Kuik F. Kuik A. Kerschbaumer A. Lauer A. Lupascu E. von Schneidemesser T. M. Butler T. M. Butler |
| author_sort | F. Kuik |
| collection | DOAJ |
| description | With NO<sub>2</sub> limit values being frequently exceeded in European cities,
complying with the European air quality regulations still poses a problem for
many cities. Traffic is typically a major source of NO<sub><i>x</i></sub> emissions
in urban areas. High-resolution chemistry transport modelling can help to
assess the impact of high urban NO<sub><i>x</i></sub> emissions on air quality
inside and outside of urban areas. However, many modelling studies report an
underestimation of modelled NO<sub><i>x</i></sub> and NO<sub>2</sub> compared with
observations. Part of this model bias has been attributed to an
underestimation of NO<sub><i>x</i></sub> emissions, particularly in urban areas.
This is consistent with recent measurement studies quantifying
underestimations of urban NO<sub><i>x</i></sub> emissions by current emission
inventories, identifying the largest discrepancies when the contribution of
traffic NO<sub><i>x</i></sub> emissions is high. This study applies a
high-resolution chemistry transport model in combination with ambient
measurements in order to assess the potential underestimation of traffic
NO<sub><i>x</i></sub> emissions in a frequently used emission inventory. The
emission inventory is based on officially reported values and the
Berlin–Brandenburg area in Germany is used as a case study. The WRF-Chem
model is used at a 3 km × 3 km horizontal resolution, simulating
the whole year of 2014. The emission data are downscaled from an original
resolution of ca. 7 km × 7 km to a resolution of
1 km × 1 km. An in-depth model evaluation including spectral
decomposition of observed and modelled time series and error apportionment
suggests that an underestimation in traffic emissions is likely one of the
main causes of the bias in modelled NO<sub>2</sub> concentrations in the urban
background, where NO<sub>2</sub> concentrations are underestimated by ca.
8 µg m<sup>−3</sup> (−30 %) on average over the whole year.
Furthermore, a diurnal cycle of the bias in modelled NO<sub>2</sub> suggests
that a more realistic treatment of the diurnal cycle of traffic emissions
might be needed. Model problems in simulating the correct mixing in the urban
planetary boundary layer probably play an important role in contributing to
the model bias, particularly in summer. Also taking into account this and
other possible sources of model bias, a correction factor for traffic
NO<sub><i>x</i></sub> emissions of ca. 3 is estimated for weekday daytime traffic
emissions in the core urban area, which corresponds to an overall
underestimation of traffic NO<sub><i>x</i></sub> emissions in the core urban area
of ca. 50 %. Sensitivity simulations for the months of January and July
using the calculated correction factor show that the weekday model bias can
be improved from −8.8 µg m<sup>−3</sup> (−26 %) to
−5.4 µg m<sup>−3</sup> (−16 %) in January on average in the urban
background, and −10.3 µg m<sup>−3</sup> (−46 %) to
−7.6 µg m<sup>−3</sup> (−34 %) in July. In addition, the negative
bias of weekday NO<sub>2</sub> concentrations downwind of the city in the rural
and suburban background can be reduced from −3.4 µg m<sup>−3</sup>
(−12 %) to −1.2 µg m<sup>−3</sup> (−4 %) in January and from
−3.0 µg m<sup>−3</sup> (−22 %) to −1.9 µg m<sup>−3</sup>
(−14 %) in July. The results and their consistency with findings from
other studies suggest that more research is needed in order to more
accurately understand the spatial and temporal variability in real-world
NO<sub><i>x</i></sub> emissions from traffic, and apply this understanding to the
inventories used in high-resolution chemical transport models. |
| first_indexed | 2024-04-12T06:15:33Z |
| format | Article |
| id | doaj.art-faf1764f4fac48c4bb85255ec3c0cac4 |
| institution | Directory Open Access Journal |
| issn | 1680-7316 1680-7324 |
| language | English |
| last_indexed | 2024-04-12T06:15:33Z |
| publishDate | 2018-06-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Chemistry and Physics |
| spelling | doaj.art-faf1764f4fac48c4bb85255ec3c0cac42022-12-22T03:44:31ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242018-06-01188203822510.5194/acp-18-8203-2018Top–down quantification of NO<sub><i>x</i></sub> emissions from traffic in an urban area using a high-resolution regional atmospheric chemistry modelF. Kuik0F. Kuik1A. Kerschbaumer2A. Lauer3A. Lupascu4E. von Schneidemesser5T. M. Butler6T. M. Butler7Institute for Advanced Sustainability Studies, Potsdam, GermanyFreie Universität, Fachbereich Geowissenschaften, Institut für Meteorologie, Berlin, GermanySenatsverwaltung für Umwelt, Verkehr und Klimaschutz Berlin, Berlin, GermanyDeutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, GermanyInstitute for Advanced Sustainability Studies, Potsdam, GermanyInstitute for Advanced Sustainability Studies, Potsdam, GermanyInstitute for Advanced Sustainability Studies, Potsdam, GermanyFreie Universität, Fachbereich Geowissenschaften, Institut für Meteorologie, Berlin, GermanyWith NO<sub>2</sub> limit values being frequently exceeded in European cities, complying with the European air quality regulations still poses a problem for many cities. Traffic is typically a major source of NO<sub><i>x</i></sub> emissions in urban areas. High-resolution chemistry transport modelling can help to assess the impact of high urban NO<sub><i>x</i></sub> emissions on air quality inside and outside of urban areas. However, many modelling studies report an underestimation of modelled NO<sub><i>x</i></sub> and NO<sub>2</sub> compared with observations. Part of this model bias has been attributed to an underestimation of NO<sub><i>x</i></sub> emissions, particularly in urban areas. This is consistent with recent measurement studies quantifying underestimations of urban NO<sub><i>x</i></sub> emissions by current emission inventories, identifying the largest discrepancies when the contribution of traffic NO<sub><i>x</i></sub> emissions is high. This study applies a high-resolution chemistry transport model in combination with ambient measurements in order to assess the potential underestimation of traffic NO<sub><i>x</i></sub> emissions in a frequently used emission inventory. The emission inventory is based on officially reported values and the Berlin–Brandenburg area in Germany is used as a case study. The WRF-Chem model is used at a 3 km × 3 km horizontal resolution, simulating the whole year of 2014. The emission data are downscaled from an original resolution of ca. 7 km × 7 km to a resolution of 1 km × 1 km. An in-depth model evaluation including spectral decomposition of observed and modelled time series and error apportionment suggests that an underestimation in traffic emissions is likely one of the main causes of the bias in modelled NO<sub>2</sub> concentrations in the urban background, where NO<sub>2</sub> concentrations are underestimated by ca. 8 µg m<sup>−3</sup> (−30 %) on average over the whole year. Furthermore, a diurnal cycle of the bias in modelled NO<sub>2</sub> suggests that a more realistic treatment of the diurnal cycle of traffic emissions might be needed. Model problems in simulating the correct mixing in the urban planetary boundary layer probably play an important role in contributing to the model bias, particularly in summer. Also taking into account this and other possible sources of model bias, a correction factor for traffic NO<sub><i>x</i></sub> emissions of ca. 3 is estimated for weekday daytime traffic emissions in the core urban area, which corresponds to an overall underestimation of traffic NO<sub><i>x</i></sub> emissions in the core urban area of ca. 50 %. Sensitivity simulations for the months of January and July using the calculated correction factor show that the weekday model bias can be improved from −8.8 µg m<sup>−3</sup> (−26 %) to −5.4 µg m<sup>−3</sup> (−16 %) in January on average in the urban background, and −10.3 µg m<sup>−3</sup> (−46 %) to −7.6 µg m<sup>−3</sup> (−34 %) in July. In addition, the negative bias of weekday NO<sub>2</sub> concentrations downwind of the city in the rural and suburban background can be reduced from −3.4 µg m<sup>−3</sup> (−12 %) to −1.2 µg m<sup>−3</sup> (−4 %) in January and from −3.0 µg m<sup>−3</sup> (−22 %) to −1.9 µg m<sup>−3</sup> (−14 %) in July. The results and their consistency with findings from other studies suggest that more research is needed in order to more accurately understand the spatial and temporal variability in real-world NO<sub><i>x</i></sub> emissions from traffic, and apply this understanding to the inventories used in high-resolution chemical transport models.https://www.atmos-chem-phys.net/18/8203/2018/acp-18-8203-2018.pdf |
| spellingShingle | F. Kuik F. Kuik A. Kerschbaumer A. Lauer A. Lupascu E. von Schneidemesser T. M. Butler T. M. Butler Top–down quantification of NO<sub><i>x</i></sub> emissions from traffic in an urban area using a high-resolution regional atmospheric chemistry model Atmospheric Chemistry and Physics |
| title | Top–down quantification of NO<sub><i>x</i></sub> emissions from traffic in an urban area using a high-resolution regional atmospheric chemistry model |
| title_full | Top–down quantification of NO<sub><i>x</i></sub> emissions from traffic in an urban area using a high-resolution regional atmospheric chemistry model |
| title_fullStr | Top–down quantification of NO<sub><i>x</i></sub> emissions from traffic in an urban area using a high-resolution regional atmospheric chemistry model |
| title_full_unstemmed | Top–down quantification of NO<sub><i>x</i></sub> emissions from traffic in an urban area using a high-resolution regional atmospheric chemistry model |
| title_short | Top–down quantification of NO<sub><i>x</i></sub> emissions from traffic in an urban area using a high-resolution regional atmospheric chemistry model |
| title_sort | top down quantification of no sub i x i sub emissions from traffic in an urban area using a high resolution regional atmospheric chemistry model |
| url | https://www.atmos-chem-phys.net/18/8203/2018/acp-18-8203-2018.pdf |
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