Articles | Volume 15, issue 3
https://doi.org/10.5194/acp-15-1539-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-15-1539-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Modelling street level PM10 concentrations across Europe: source apportionment and possible futures
G. Kiesewetter
CORRESPONDING AUTHOR
International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1, A-2361 Laxenburg, Austria
J. Borken-Kleefeld
International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1, A-2361 Laxenburg, Austria
W. Schöpp
International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1, A-2361 Laxenburg, Austria
International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1, A-2361 Laxenburg, Austria
P. Thunis
Joint Research Centre, Institute for Environment and Sustainability (JRC-IES), Ispra, Italy
B. Bessagnet
National Institute for Environment and Risks (INERIS), Paris, France
E. Terrenoire
National Institute for Environment and Risks (INERIS), Paris, France
H. Fagerli
Norwegian Meteorological Institute, Oslo, Norway
A. Nyiri
Norwegian Meteorological Institute, Oslo, Norway
M. Amann
International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1, A-2361 Laxenburg, Austria
Viewed
Total article views: 15,261 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 10 Jul 2014)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
7,457 | 7,062 | 742 | 15,261 | 147 | 175 |
- HTML: 7,457
- PDF: 7,062
- XML: 742
- Total: 15,261
- BibTeX: 147
- EndNote: 175
Total article views: 14,490 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 13 Feb 2015)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
7,025 | 6,750 | 715 | 14,490 | 136 | 169 |
- HTML: 7,025
- PDF: 6,750
- XML: 715
- Total: 14,490
- BibTeX: 136
- EndNote: 169
Total article views: 771 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 10 Jul 2014)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
432 | 312 | 27 | 771 | 11 | 6 |
- HTML: 432
- PDF: 312
- XML: 27
- Total: 771
- BibTeX: 11
- EndNote: 6
Cited
58 citations as recorded by crossref.
- Cost-efficient strategy for reducing PM 2.5 levels in the Tokyo metropolitan area: An integrated approach with air quality and economic models Y. Kunugi et al. 10.1371/journal.pone.0207623
- A statistical physics approach to perform fast highly-resolved air quality simulations – A new step towards the meta-modelling of chemistry transport models B. Bessagnet et al. 10.1016/j.envsoft.2019.02.017
- The haze problem in Northern Thailand and policies to combat it: A review J. Moran et al. 10.1016/j.envsci.2019.03.016
- Design and implementation of a new module to evaluate the cost of air pollutant abatement measures B. Bessagnet et al. 10.1016/j.jenvman.2022.115486
- The influence of dust on extreme precipitation at a large city in North China T. Feng et al. 10.1016/j.scitotenv.2023.165890
- Explaining the high PM10 concentrations observed in Polish urban areas M. Reizer & K. Juda-Rezler 10.1007/s11869-015-0358-z
- Presentation of the EURODELTA III intercomparison exercise – evaluation of the chemistry transport models' performance on criteria pollutants and joint analysis with meteorology B. Bessagnet et al. 10.5194/acp-16-12667-2016
- Long-range and local air pollution: what can we learn from chemical speciation of particulate matter at paired sites? M. Pandolfi et al. 10.5194/acp-20-409-2020
- Prediction of source contributions to urban background PM<sub>10</sub> concentrations in European cities: a case study for an episode in December 2016 using EMEP/MSC-W rv4.15 – Part 2: The city contribution M. Pommier 10.5194/gmd-14-4143-2021
- The influence of residential and workday population mobility on exposure to air pollution in the UK S. Reis et al. 10.1016/j.envint.2018.10.005
- How does a social practice perspective add to the development of policy instruments to reduce consumption-based CO2 emissions? A case study of Austria M. Kammerlander et al. 10.1080/14693062.2020.1727830
- Source apportionment and sensitivity analysis: two methodologies with two different purposes A. Clappier et al. 10.5194/gmd-10-4245-2017
- Air pollution and child health impacts of decarbonization in 16 global cities: Modelling study J. Milner et al. 10.1016/j.envint.2023.107972
- Prediction of source contributions to urban background PM<sub>10</sub> concentrations in European cities: a case study for an episode in December 2016 using EMEP/MSC-W rv4.15 and LOTOS-EUROS v2.0 – Part 1: The country contributions M. Pommier et al. 10.5194/gmd-13-1787-2020
- A resource-efficient and sufficient future mobility system for improved well-being in Europe M. Kammerlander et al. 10.1007/s40309-015-0065-x
- TM5-FASST: a global atmospheric source–receptor model for rapid impact analysis of emission changes on air quality and short-lived climate pollutants R. Van Dingenen et al. 10.5194/acp-18-16173-2018
- On the design and assessment of regional air quality plans: The SHERPA approach P. Thunis et al. 10.1016/j.jenvman.2016.09.049
- Mitigation pathways of air pollution from residential emissions in the Beijing-Tianjin-Hebei region in China J. Liu et al. 10.1016/j.envint.2018.09.059
- Emerging miniaturized technologies for airborne particulate matter pervasive monitoring M. Carminati et al. 10.1016/j.measurement.2015.12.028
- VARIATION OF PM10 CONCENTRATION DEPENDING ON THE METEOROLOGICAL PARAMETERS IN TWO BUCHAREST MONITORING STATIONS (IN GREEN AREAS) K. Bodor et al. 10.15551/pesd2020141022
- Reducing global air pollution: the scope for further policy interventions M. Amann et al. 10.1098/rsta.2019.0331
- On the validity of the incremental approach to estimate the impact of cities on air quality P. Thunis 10.1016/j.atmosenv.2017.11.012
- Modelling PM2.5 impact indicators in Europe: Health effects and legal compliance G. Kiesewetter et al. 10.1016/j.envsoft.2015.02.022
- Aerosol pollution, including eroded soils, intensifies cloud growth, precipitation, and soil erosion: A review M. Casazza et al. 10.1016/j.jclepro.2018.04.004
- A decision framework for Integrated Assessment Modelling of air quality at regional and local scale G. Guariso et al. 10.1016/j.envsci.2016.05.001
- On the urban geometry generalization for CFD simulation of gas dispersion from chimneys: Comparison with Gaussian plume model F. Toja-Silva et al. 10.1016/j.jweia.2018.04.003
- Development of a versatile source apportionment analysis based on positive matrix factorization: a case study of the seasonal variation of organic aerosol sources in Estonia A. Vlachou et al. 10.5194/acp-19-7279-2019
- Impact of 2020 COVID-19 lockdowns on particulate air pollution across Europe J. Putaud et al. 10.5194/acp-23-10145-2023
- Comparison of two methods of calculating NO2 and PM10 transboundary pollution by CMAQ chemical transport model and the assessment of the non-linearity effect D. Štefánik et al. 10.1016/j.apr.2020.02.012
- Connecting air quality regulating ecosystem services with beneficiaries through quantitative serviceshed analysis M. Charles et al. 10.1016/j.ecoser.2019.101057
- The impact of Swedish SO2 policy instruments on SO2 emissions 1990–2012 S. Åström et al. 10.1016/j.envsci.2017.07.014
- Lung Cancer Risk Associated with Exposure to Benzo(A)Pyrene in Polish Agglomerations, Cities, and Other Areas K. Widziewicz et al. 10.1007/s41742-017-0061-z
- Managing future air quality in megacities: A case study for Delhi M. Amann et al. 10.1016/j.atmosenv.2017.04.041
- Ammonia emission time profiles based on manure transport data improve ammonia modelling across north western Europe C. Hendriks et al. 10.1016/j.atmosenv.2016.01.043
- BAERLIN2014 – the influence of land surface types on and the horizontal heterogeneity of air pollutant levels in Berlin B. Bonn et al. 10.5194/acp-16-7785-2016
- Burden of Mortality and Disease Attributable to Multiple Air Pollutants in Warsaw, Poland P. Holnicki et al. 10.3390/ijerph14111359
- Air quality and health effects of a transition to ammonia–fueled shipping in Singapore S. Rathod et al. 10.1088/2752-5309/acfb2e
- Mitigation pathways towards national ambient air quality standards in India P. Purohit et al. 10.1016/j.envint.2019.105147
- Land Use and the Climatic Determinants of Population Exposure to PM2.5 in Central Bangladesh M. Hassan et al. 10.3390/pollutants3030026
- Source apportionment of air pollution in European urban areas: Lessons from the ClairCity project S. Coelho et al. 10.1016/j.jenvman.2022.115899
- Modelling Hourly Particulate Matter (PM10) Concentrations at High Spatial Resolution in Germany Using Land Use Regression and Open Data S. Wallek et al. 10.3390/atmos13081282
- Meteorologically normalized spatial and temporal variations investigation using a machine learning-random forest model in criteria pollutants across Tehran, Iran M. Ali-Taleshi et al. 10.1016/j.uclim.2023.101790
- PM2.5 source allocation in European cities: A SHERPA modelling study P. Thunis et al. 10.1016/j.atmosenv.2018.05.062
- Good Practices on Air Quality, Pollution and Health Impact at EU Level M. Daniela-Ioana et al. 10.24818/EA/2020/53/256
- Mapping and Understanding Patterns of Air Quality Using Satellite Data and Machine Learning R. Stirnberg et al. 10.1029/2019JD031380
- The UK particulate matter air pollution episode of March–April 2014: more than Saharan dust M. Vieno et al. 10.1088/1748-9326/11/4/044004
- Comparison of source apportionment approaches and analysis of non-linearity in a real case model application C. Belis et al. 10.5194/gmd-14-4731-2021
- Beyond the Energy System: Modeling Frameworks Depicting Distributional Impacts for Interdisciplinary Policy Analysis R. Montenegro et al. 10.1002/ente.202000668
- Source apportionment to support air quality planning: Strengths and weaknesses of existing approaches P. Thunis et al. 10.1016/j.envint.2019.05.019
- Why is the city's responsibility for its air pollution often underestimated? A focus on PM<sub>2.5</sub> P. Thunis et al. 10.5194/acp-21-18195-2021
- Meteorology-driven variability of air pollution (PM<sub>1</sub>) revealed with explainable machine learning R. Stirnberg et al. 10.5194/acp-21-3919-2021
- Background Influence of PM2.5 in Dallas–Fort Worth Area and Recommendations for Source Apportionment A. Shapero et al. 10.3390/air1040019
- Characterization of haze episodes and factors contributing to their formation using a panel model X. Zhang et al. 10.1016/j.chemosphere.2016.01.090
- Perspectives on using cost-benefit analysis to set environmental targets – a compilation and discussion of arguments informed by the process leading to the 2016 EU air pollution emission targets S. Åström 10.1016/j.eiar.2022.106941
- Cost-effective reductions of PM2.5 concentrations and exposure in Italy A. Ciucci et al. 10.1016/j.atmosenv.2016.05.049
- Urban environment as a factor modulating metals deposition in the respiratory track and associated cancer risk K. Widziewicz & W. Rogula-Kozłowska 10.1016/j.apr.2017.11.005
- An urban scale application and validation of the CALPUFF model P. Holnicki et al. 10.1016/j.apr.2015.10.016
- REDUCING THE POLLUTION OF THE AIRSPACE OF THE CITY'S MAIN HIGHWAY AREAS H. TATARCHENKO et al. 10.33543/120230153157
56 citations as recorded by crossref.
- Cost-efficient strategy for reducing PM 2.5 levels in the Tokyo metropolitan area: An integrated approach with air quality and economic models Y. Kunugi et al. 10.1371/journal.pone.0207623
- A statistical physics approach to perform fast highly-resolved air quality simulations – A new step towards the meta-modelling of chemistry transport models B. Bessagnet et al. 10.1016/j.envsoft.2019.02.017
- The haze problem in Northern Thailand and policies to combat it: A review J. Moran et al. 10.1016/j.envsci.2019.03.016
- Design and implementation of a new module to evaluate the cost of air pollutant abatement measures B. Bessagnet et al. 10.1016/j.jenvman.2022.115486
- The influence of dust on extreme precipitation at a large city in North China T. Feng et al. 10.1016/j.scitotenv.2023.165890
- Explaining the high PM10 concentrations observed in Polish urban areas M. Reizer & K. Juda-Rezler 10.1007/s11869-015-0358-z
- Presentation of the EURODELTA III intercomparison exercise – evaluation of the chemistry transport models' performance on criteria pollutants and joint analysis with meteorology B. Bessagnet et al. 10.5194/acp-16-12667-2016
- Long-range and local air pollution: what can we learn from chemical speciation of particulate matter at paired sites? M. Pandolfi et al. 10.5194/acp-20-409-2020
- Prediction of source contributions to urban background PM<sub>10</sub> concentrations in European cities: a case study for an episode in December 2016 using EMEP/MSC-W rv4.15 – Part 2: The city contribution M. Pommier 10.5194/gmd-14-4143-2021
- The influence of residential and workday population mobility on exposure to air pollution in the UK S. Reis et al. 10.1016/j.envint.2018.10.005
- How does a social practice perspective add to the development of policy instruments to reduce consumption-based CO2 emissions? A case study of Austria M. Kammerlander et al. 10.1080/14693062.2020.1727830
- Source apportionment and sensitivity analysis: two methodologies with two different purposes A. Clappier et al. 10.5194/gmd-10-4245-2017
- Air pollution and child health impacts of decarbonization in 16 global cities: Modelling study J. Milner et al. 10.1016/j.envint.2023.107972
- Prediction of source contributions to urban background PM<sub>10</sub> concentrations in European cities: a case study for an episode in December 2016 using EMEP/MSC-W rv4.15 and LOTOS-EUROS v2.0 – Part 1: The country contributions M. Pommier et al. 10.5194/gmd-13-1787-2020
- A resource-efficient and sufficient future mobility system for improved well-being in Europe M. Kammerlander et al. 10.1007/s40309-015-0065-x
- TM5-FASST: a global atmospheric source–receptor model for rapid impact analysis of emission changes on air quality and short-lived climate pollutants R. Van Dingenen et al. 10.5194/acp-18-16173-2018
- On the design and assessment of regional air quality plans: The SHERPA approach P. Thunis et al. 10.1016/j.jenvman.2016.09.049
- Mitigation pathways of air pollution from residential emissions in the Beijing-Tianjin-Hebei region in China J. Liu et al. 10.1016/j.envint.2018.09.059
- Emerging miniaturized technologies for airborne particulate matter pervasive monitoring M. Carminati et al. 10.1016/j.measurement.2015.12.028
- VARIATION OF PM10 CONCENTRATION DEPENDING ON THE METEOROLOGICAL PARAMETERS IN TWO BUCHAREST MONITORING STATIONS (IN GREEN AREAS) K. Bodor et al. 10.15551/pesd2020141022
- Reducing global air pollution: the scope for further policy interventions M. Amann et al. 10.1098/rsta.2019.0331
- On the validity of the incremental approach to estimate the impact of cities on air quality P. Thunis 10.1016/j.atmosenv.2017.11.012
- Modelling PM2.5 impact indicators in Europe: Health effects and legal compliance G. Kiesewetter et al. 10.1016/j.envsoft.2015.02.022
- Aerosol pollution, including eroded soils, intensifies cloud growth, precipitation, and soil erosion: A review M. Casazza et al. 10.1016/j.jclepro.2018.04.004
- A decision framework for Integrated Assessment Modelling of air quality at regional and local scale G. Guariso et al. 10.1016/j.envsci.2016.05.001
- On the urban geometry generalization for CFD simulation of gas dispersion from chimneys: Comparison with Gaussian plume model F. Toja-Silva et al. 10.1016/j.jweia.2018.04.003
- Development of a versatile source apportionment analysis based on positive matrix factorization: a case study of the seasonal variation of organic aerosol sources in Estonia A. Vlachou et al. 10.5194/acp-19-7279-2019
- Impact of 2020 COVID-19 lockdowns on particulate air pollution across Europe J. Putaud et al. 10.5194/acp-23-10145-2023
- Comparison of two methods of calculating NO2 and PM10 transboundary pollution by CMAQ chemical transport model and the assessment of the non-linearity effect D. Štefánik et al. 10.1016/j.apr.2020.02.012
- Connecting air quality regulating ecosystem services with beneficiaries through quantitative serviceshed analysis M. Charles et al. 10.1016/j.ecoser.2019.101057
- The impact of Swedish SO2 policy instruments on SO2 emissions 1990–2012 S. Åström et al. 10.1016/j.envsci.2017.07.014
- Lung Cancer Risk Associated with Exposure to Benzo(A)Pyrene in Polish Agglomerations, Cities, and Other Areas K. Widziewicz et al. 10.1007/s41742-017-0061-z
- Managing future air quality in megacities: A case study for Delhi M. Amann et al. 10.1016/j.atmosenv.2017.04.041
- Ammonia emission time profiles based on manure transport data improve ammonia modelling across north western Europe C. Hendriks et al. 10.1016/j.atmosenv.2016.01.043
- BAERLIN2014 – the influence of land surface types on and the horizontal heterogeneity of air pollutant levels in Berlin B. Bonn et al. 10.5194/acp-16-7785-2016
- Burden of Mortality and Disease Attributable to Multiple Air Pollutants in Warsaw, Poland P. Holnicki et al. 10.3390/ijerph14111359
- Air quality and health effects of a transition to ammonia–fueled shipping in Singapore S. Rathod et al. 10.1088/2752-5309/acfb2e
- Mitigation pathways towards national ambient air quality standards in India P. Purohit et al. 10.1016/j.envint.2019.105147
- Land Use and the Climatic Determinants of Population Exposure to PM2.5 in Central Bangladesh M. Hassan et al. 10.3390/pollutants3030026
- Source apportionment of air pollution in European urban areas: Lessons from the ClairCity project S. Coelho et al. 10.1016/j.jenvman.2022.115899
- Modelling Hourly Particulate Matter (PM10) Concentrations at High Spatial Resolution in Germany Using Land Use Regression and Open Data S. Wallek et al. 10.3390/atmos13081282
- Meteorologically normalized spatial and temporal variations investigation using a machine learning-random forest model in criteria pollutants across Tehran, Iran M. Ali-Taleshi et al. 10.1016/j.uclim.2023.101790
- PM2.5 source allocation in European cities: A SHERPA modelling study P. Thunis et al. 10.1016/j.atmosenv.2018.05.062
- Good Practices on Air Quality, Pollution and Health Impact at EU Level M. Daniela-Ioana et al. 10.24818/EA/2020/53/256
- Mapping and Understanding Patterns of Air Quality Using Satellite Data and Machine Learning R. Stirnberg et al. 10.1029/2019JD031380
- The UK particulate matter air pollution episode of March–April 2014: more than Saharan dust M. Vieno et al. 10.1088/1748-9326/11/4/044004
- Comparison of source apportionment approaches and analysis of non-linearity in a real case model application C. Belis et al. 10.5194/gmd-14-4731-2021
- Beyond the Energy System: Modeling Frameworks Depicting Distributional Impacts for Interdisciplinary Policy Analysis R. Montenegro et al. 10.1002/ente.202000668
- Source apportionment to support air quality planning: Strengths and weaknesses of existing approaches P. Thunis et al. 10.1016/j.envint.2019.05.019
- Why is the city's responsibility for its air pollution often underestimated? A focus on PM<sub>2.5</sub> P. Thunis et al. 10.5194/acp-21-18195-2021
- Meteorology-driven variability of air pollution (PM<sub>1</sub>) revealed with explainable machine learning R. Stirnberg et al. 10.5194/acp-21-3919-2021
- Background Influence of PM2.5 in Dallas–Fort Worth Area and Recommendations for Source Apportionment A. Shapero et al. 10.3390/air1040019
- Characterization of haze episodes and factors contributing to their formation using a panel model X. Zhang et al. 10.1016/j.chemosphere.2016.01.090
- Perspectives on using cost-benefit analysis to set environmental targets – a compilation and discussion of arguments informed by the process leading to the 2016 EU air pollution emission targets S. Åström 10.1016/j.eiar.2022.106941
- Cost-effective reductions of PM2.5 concentrations and exposure in Italy A. Ciucci et al. 10.1016/j.atmosenv.2016.05.049
- Urban environment as a factor modulating metals deposition in the respiratory track and associated cancer risk K. Widziewicz & W. Rogula-Kozłowska 10.1016/j.apr.2017.11.005
Saved (final revised paper)
Saved (preprint)
Discussed (final revised paper)
Discussed (final revised paper)
Latest update: 15 Nov 2024
Short summary
We describe the multi-stage approach applied in the GAINS model to assess compliance with PM10 limit values at more than 1850 individual air quality monitoring stations in Europe. We analyse source contributions to ambient concentrations and the implications of future policy choices on air quality for 2030. While current legislation does not solve compliance issues, problems are largely eliminated by EU-wide adoption of the best available emission control technology.
We describe the multi-stage approach applied in the GAINS model to assess compliance with PM10...
Altmetrics
Final-revised paper
Preprint