Articles | Volume 13, issue 8
https://doi.org/10.5194/amt-13-4601-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-13-4601-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Aug 2020
Research article |
| 26 Aug 2020
| 26 Aug 2020
High-resolution mapping of urban air quality with heterogeneous observations: a new methodology and its application to Amsterdam
Royal Netherlands Meteorological Institute (KNMI), Postbus 201, 3730
AE, De Bilt, the Netherlands
Viewed
Total article views: 4,881 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 17 Dec 2019)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 3,400 | 1,361 | 120 | 4,881 | 244 | 159 | 170 |
- HTML: 3,400
- PDF: 1,361
- XML: 120
- Total: 4,881
- Supplement: 244
- BibTeX: 159
- EndNote: 170
Total article views: 4,156 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 26 Aug 2020)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 3,079 | 974 | 103 | 4,156 | 244 | 134 | 146 |
- HTML: 3,079
- PDF: 974
- XML: 103
- Total: 4,156
- Supplement: 244
- BibTeX: 134
- EndNote: 146
Total article views: 725 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 17 Dec 2019)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 321 | 387 | 17 | 725 | 25 | 24 |
- HTML: 321
- PDF: 387
- XML: 17
- Total: 725
- BibTeX: 25
- EndNote: 24
Viewed (geographical distribution)
Total article views: 4,881 (including HTML, PDF, and XML)
Thereof 4,564 with geography defined
and 317 with unknown origin.
Total article views: 4,156 (including HTML, PDF, and XML)
Thereof 3,901 with geography defined
and 255 with unknown origin.
Total article views: 725 (including HTML, PDF, and XML)
Thereof 663 with geography defined
and 62 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
24 citations as recorded by crossref.
- Biodiversity modeling to manage urban ecosystems for people and nature J. Casanelles-Abella et al.
- Short-term NO2 exposure and cognitive and mental health: A panel study based on a citizen science project in Barcelona, Spain F. Gignac et al.
- Deployment and Evaluation of a Network of Open Low-Cost Air Quality Sensor Systems P. Schneider et al.
- Building-resolving simulations of anthropogenic and biospheric CO2 in the city of Zurich with GRAMM/GRAL D. Brunner et al.
- Multiscale and multisource data fusion for full-coverage PM2.5 concentration mapping: Can spatial pattern recognition come with modeling accuracy? K. Bai et al.
- Integration of Data and Predictive Models for the Evaluation of Air Quality and Noise in Urban Environments J. Govea et al.
- Data Assimilation Algorithms for Atmospheric Chemistry Models A. Penenko et al.
- Sensitivity Operator Framework for Analyzing Heterogeneous Air Quality Monitoring Systems A. Penenko et al.
- A machine learning-based approach for fusing measurements from standard sites, low-cost sensors, and satellite retrievals: Application to NO2 pollution hotspot identification J. Fu et al.
- Empowering communities: Advancements in air quality monitoring and citizen engagement H. Relvas et al.
- Irregular Area Cartograms for Local-Level Presentation of Selected SDGs Indicators Based on Earth Observation Data A. Markowska & D. Dukaczewski
- Towards integration of LOTOS-EUROS high resolution simulations and heterogenous low-cost sensor observations I. Skoulidou et al.
- Data fusion for enhancing urban air quality modeling using large-scale citizen science data A. O'Regan et al.
- Health burden and inequities of urban environmental stressors in Sofia, Bulgaria S. Khomenko et al.
- Data fusion uncertainty-enabled methods to map street-scale hourly NO2 in Barcelona: a case study with CALIOPE-Urban v1.0 A. Criado et al.
- High-resolution mapping of urban NO2 concentrations using Retina v2: a case study on data assimilation of surface and satellite observations in Madrid B. Mijling et al.
- Data fusion of sparse, heterogeneous, and mobile sensor devices using adaptive distance attention J. Lepioufle et al.
- Street- and census-level NO2 data for Barcelona with uncertainty and exceedance probability mapping A. Criado et al.
- High-resolution mapping of urban air quality with heterogeneous observations: a new methodology and its application to Amsterdam B. Mijling
- Design and Implementation of a Low-Cost Air Quality Network for the Aburra Valley Surrounding Mountains A. Yarce Botero et al.
- Satellite-based assessment of national carbon monoxide concentrations for air quality reporting in Finland T. Karppinen et al.
- Agent-based modelling: A stochastic approach to assessing personal exposure to environmental pollutants – Insights from the URBANOME project A. Karakoltzidis et al.
- Evolving trends in application of low-cost air quality sensor networks: challenges and future directions E. Bagkis et al.
- High-resolution ground NO2 estimation at hyperlocal level using deep learning with Sentinel-2 and Sentinel-5P data S. Khan et al.
24 citations as recorded by crossref.
- Biodiversity modeling to manage urban ecosystems for people and nature J. Casanelles-Abella et al.
- Short-term NO2 exposure and cognitive and mental health: A panel study based on a citizen science project in Barcelona, Spain F. Gignac et al.
- Deployment and Evaluation of a Network of Open Low-Cost Air Quality Sensor Systems P. Schneider et al.
- Building-resolving simulations of anthropogenic and biospheric CO2 in the city of Zurich with GRAMM/GRAL D. Brunner et al.
- Multiscale and multisource data fusion for full-coverage PM2.5 concentration mapping: Can spatial pattern recognition come with modeling accuracy? K. Bai et al.
- Integration of Data and Predictive Models for the Evaluation of Air Quality and Noise in Urban Environments J. Govea et al.
- Data Assimilation Algorithms for Atmospheric Chemistry Models A. Penenko et al.
- Sensitivity Operator Framework for Analyzing Heterogeneous Air Quality Monitoring Systems A. Penenko et al.
- A machine learning-based approach for fusing measurements from standard sites, low-cost sensors, and satellite retrievals: Application to NO2 pollution hotspot identification J. Fu et al.
- Empowering communities: Advancements in air quality monitoring and citizen engagement H. Relvas et al.
- Irregular Area Cartograms for Local-Level Presentation of Selected SDGs Indicators Based on Earth Observation Data A. Markowska & D. Dukaczewski
- Towards integration of LOTOS-EUROS high resolution simulations and heterogenous low-cost sensor observations I. Skoulidou et al.
- Data fusion for enhancing urban air quality modeling using large-scale citizen science data A. O'Regan et al.
- Health burden and inequities of urban environmental stressors in Sofia, Bulgaria S. Khomenko et al.
- Data fusion uncertainty-enabled methods to map street-scale hourly NO2 in Barcelona: a case study with CALIOPE-Urban v1.0 A. Criado et al.
- High-resolution mapping of urban NO2 concentrations using Retina v2: a case study on data assimilation of surface and satellite observations in Madrid B. Mijling et al.
- Data fusion of sparse, heterogeneous, and mobile sensor devices using adaptive distance attention J. Lepioufle et al.
- Street- and census-level NO2 data for Barcelona with uncertainty and exceedance probability mapping A. Criado et al.
- High-resolution mapping of urban air quality with heterogeneous observations: a new methodology and its application to Amsterdam B. Mijling
- Design and Implementation of a Low-Cost Air Quality Network for the Aburra Valley Surrounding Mountains A. Yarce Botero et al.
- Satellite-based assessment of national carbon monoxide concentrations for air quality reporting in Finland T. Karppinen et al.
- Agent-based modelling: A stochastic approach to assessing personal exposure to environmental pollutants – Insights from the URBANOME project A. Karakoltzidis et al.
- Evolving trends in application of low-cost air quality sensor networks: challenges and future directions E. Bagkis et al.
- High-resolution ground NO2 estimation at hyperlocal level using deep learning with Sentinel-2 and Sentinel-5P data S. Khan et al.
Saved (final revised paper)
Latest update: 11 May 2026
Short summary
Many cities are experimenting with networks of low-cost sensors, complementary to their reference stations. Often the observations are published as dots on a map, as spatial interpolation is far from trivial. A new methodology to assimilate observations of different accuracy in a generic urban-air-quality model is introduced. It can be used for mapping local air quality based on reference measurements only or as a framework to integrate low-cost measurements next to official measurements.
Many cities are experimenting with networks of low-cost sensors, complementary to their...
