The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
CAMS-REG-v4: a state-of-the-art high-resolution European emission inventory for air quality modelling
Open accessAbstract
Abstract. This paper presents a state-of-the-art anthropogenic emission inventory developed for the European domain for an 18-year time series (2000–2017) at a 0.05∘ × 0.1∘ grid resolution, specifically designed to support air quality modelling. The main air pollutants are included: NOx, SO2, non-methane volatile organic compounds (NMVOCs), NH3, CO, PM10 and PM2.5, and also CH4. To stay as close as possible to the emissions as officially reported and used in policy assessment, the inventory uses the officially reported emission data by European countries to the UN Framework Convention on Climate Change, the Convention on Long-Range Transboundary Air Pollution and the EU National Emission Ceilings Directive as the basis where possible. Where deemed necessary because of errors, incompleteness or inconsistencies, these are replaced with or complemented by other emission data, most notably the estimates included in the Greenhouse gas Air pollution Interaction and Synergies (GAINS) model. Emissions are collected at the high sectoral level, distinguishing around 250 different sector–fuel combinations, whereafter a consistent spatial distribution is applied for Europe. A specific proxy is selected for each of the sector–fuel combinations, pollutants and years. Point source emissions are largely based on reported facility-level emissions, complemented by other sources of point source data for power plants. For specific sources, the resulting emission data were replaced with other datasets. Emissions from shipping (both inland and at sea) are based on the results from a separate shipping emission model where emissions are based on actual ship movement data, and agricultural waste burning emissions are based on satellite observations. The resulting spatially distributed emissions are evaluated against earlier versions of the dataset as well as against alternative emission estimates, which reveals specific discrepancies in some cases. Along with the resulting annual emission maps, profiles for splitting particulate matter (PM) and NMVOCs into individual components are provided, as well as information on the height profile by sector and temporal disaggregation down to the hourly level to support modelling activities. Annual grid maps are available in csv and NetCDF format (https://doi.org/10.24380/0vzb-a387, Kuenen et al., 2021).
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Cites
Kaiser, J. W., Heil, A., Andreae, M. O., Benedetti, A., Chubarova, N., Jones, L., Morcrette, J.-J., Razinger, M., Schultz, M. G., Suttie, M., et al. (2012) · Biogeosciences · doi:10.5194/bg-9-527-2012 · Cited by 1,518
Janssens-Maenhout, G., Crippa, M., Guizzardi, D., Dentener, F., Muntean, M., Pouliot, G., Keating, T., Zhang, Q., Kurokawa, J., Wankmüller, R., et al. (2015) · Atmospheric Chemistry and Physics · doi:10.5194/acp-15-11411-2015 · Cited by 978
Self-citationGridded emissions of air pollutants for the period 1970–2012 within EDGAR v4.3.2
Crippa, M., Guizzardi, D., Muntean, M., Schaaf, E., Dentener, F., van Aardenne, J. A., Monni, S., Doering, U., Olivier, J. G. J., Pagliari, V., et al. (2018) · Earth System Science Data · doi:10.5194/essd-10-1987-2018 · Cited by 889
Global anthropogenic emissions of particulate matter including black carbon
Klimont, Z., Kupiainen, K., Heyes, C., Purohit, P., Cofala, J., Rafaj, P., Borken-Kleefeld, J., & Schöpp, W. (2017) · Atmospheric Chemistry and Physics · doi:10.5194/acp-17-8681-2017 · Cited by 878
McDuffie, E. E., Smith, S. J., O'Rourke, P., Tibrewal, K., Venkataraman, C., Marais, E. A., Zheng, B., Crippa, M., Brauer, M., & Martin, R. V. (2020) · Earth System Science Data · doi:10.5194/essd-12-3413-2020 · Cited by 714
Impact of maritime transport emissions on coastal air quality in Europe
Viana, M., Hammingh, P., Colette, A., Querol, X., Degraeuwe, B., Vlieger, I. D., & van Aardenne, J. (2014) · Atmospheric Environment · doi:10.1016/j.atmosenv.2014.03.046 · Cited by 634
Global assessment of shipping emissions in 2015 on a high spatial and temporal resolution
Johansson, L., Jalkanen, J.-P., & Kukkonen, J. (2017) · Atmospheric Environment · doi:10.1016/j.atmosenv.2017.08.042 · Cited by 534
Self-citationKuenen, J. J. P., Visschedijk, A. J. H., Jozwicka, M., & Denier van der Gon, H. A. C. (2014) · Atmospheric Chemistry and Physics · doi:10.5194/acp-14-10963-2014 · Cited by 509
Self-citationJalkanen, J.-P., Johansson, L., Kukkonen, J., Brink, A., Kalli, J., & Stipa, T. (2012) · Atmospheric Chemistry and Physics · doi:10.5194/acp-12-2641-2012 · Cited by 406
Self-citationCOPERT: A European Road Transport Emission Inventory Model
Ntziachristos, L., Gkatzoflias, D., Kouridis, C., & Samaras, Z. (2009) · Environmental Science and Engineering · doi:10.1007/978-3-540-88351-7_37 · Cited by 335
Metadata
- Authors
- Kuenen, J., Dellaert, S., Visschedijk, A., Jalkanen, J.-P., Super, I., & Denier van der Gon, H.
- Venue
- Earth System Science Data
- Publisher
- Copernicus GmbH
- Published
- 2022-02-07
- Volume
- 14
- Issue
- 2
- Pages
- 491-515
- ISSN
- 1866-3508 (ISSN-L)
- 1866-3516
- OpenAlex
- W4210901135
- Cited by
- 312
- References
- 28
- FWCI
- 23.70
- Type
- journal article
- Language
- en
- Open access
- gold
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- CoChat. (2026). Citation check: CAMS-REG-v4: a state-of-the-art high-resolution European emission inventory for air quality modelling. https://app.cochat.ai/papers/10.5194/essd-14-491-2022
- The paper
- Kuenen, J., Dellaert, S., Visschedijk, A., Jalkanen, J.-P., Super, I., & Denier van der Gon, H. (2022). CAMS-REG-v4: a state-of-the-art high-resolution European emission inventory for air quality modelling. Earth System Science Data. https://doi.org/10.5194/essd-14-491-2022
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