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dc.contributor.authorGe, Yao
dc.contributor.authorHeal, Mathew R
dc.contributor.authorStevenson, David S.
dc.contributor.authorWind, Peter
dc.contributor.authorVieno, Massimo
dc.date.accessioned2022-02-15T12:04:49Z
dc.date.available2022-02-15T12:04:49Z
dc.date.issued2021-11-18
dc.description.abstractAtmospheric pollution has many profound effects on human health, ecosystems, and the climate. Of concern are high concentrations and deposition of reactive nitrogen (N<sub>r</sub>) species, especially of reduced N (gaseous NH<sub>3</sub>, particulate NH<sub>4</sub> <sup>+</sup>). Atmospheric chemistry and transport models (ACTMs) are crucial to understanding sources and impacts of N<sub>r</sub> chemistry and its potential mitigation. Here we undertake the first evaluation of the global version of the EMEP MSC-W ACTM driven by WRF meteorology (1<sup>◦</sup> × 1 <sup>◦</sup> resolution), with a focus on surface concentrations and wet deposition of N and S species relevant to investigation of atmospheric N<sub>r</sub> and secondary inorganic aerosol (SIA). The model–measurement comparison is conducted both spatially and temporally, covering 10 monitoring networks worldwide. Model simulations for 2010 compared use of both HTAP and ECLIPSE<sub>E</sub> (ECLIPSE annual total with EDGAR monthly profile) emissions inventories; those for 2015 used ECLIPSE<sub>E</sub> only. Simulations of primary pollutants are somewhat sensitive to the choice of inventory in places where regional differences in primary emissions between the two inventories are apparent (e.g. China) but are much less sensitive for secondary components. For example, the difference in modelled global annual mean surface NH<sub>3</sub> concentration using the two 2010 inventories is 18 % (HTAP: 0.26 µgm<sup>−3</sup> ; ECLIPSE<sub>E</sub>: 0.31 µgm<sup>−3</sup> ) but is only 3.5 % for NH<sub>4</sub> <sup>+</sup> (HTAP: 0.316 µgm<sup>−3</sup> ; ECLIPSE<sub>E</sub>: 0.305 µgm<sup>−3</sup> ). Comparisons of 2010 and 2015 surface concentrations between the model and measurements demonstrate that the model captures the overall spatial and seasonal variations well for the major inorganic pollutants NH<sub>3</sub>, NO<sub>2</sub>, SO<sub>2</sub>, HNO<sub>3</sub>, NH<sub>4</sub> <sup>+</sup>, NO<sub>3</sub> <sup>−</sup>, and SO<sub>4</sub> <sup>2−</sup> and their wet deposition in East Asia, Southeast Asia, Europe, and North America. The model shows better correlations with annual average measurements for networks in Southeast Asia (mean R for seven species: R<sub>7</sub> = 0.73), Europe (R<sub>7</sub> = 0.67), and North America (R<sub>7</sub> = 0.63) than in East Asia (R<sub>5</sub> = 0.35) (data for 2015), which suggests potential issues with the measurements in the latter network. Temporally, both model and measurements agree on higher NH<sub>3</sub> concentrations in spring and summer and lower concentrations in winter. The model slightly underestimates annual total precipitation measurements (by 13 %–45 %) but agrees well with the spatial variations in precipitation in all four world regions (0.65–0.94 R range). High correlations between measured and modelled NH<sub>4</sub> + precipitation concentrations are also observed in all regions except East Asia. For annual total wet deposition of reduced N, the greatest consistency is in North America (0.75–0.82 R range), followed by Southeast Asia (R = 0.68) and Europe (R = 0.61). Model–measurement bias varies between species in different networks; for example, bias for NH<sub>4</sub> <sup>+</sup> and NO<sub>3</sub> <sup>−</sup> is largest in Europe and North America and smallest in East Asia and Southeast Asia. The greater uniformity in spatial correlations than in biases suggests that the major driver of model–measurement discrepancies (aside from differing spatial representativeness and uncertainties and biases in measurements) are shortcomings in absolute emissions rather than in modelling the atmospheric processes. The comprehensive evaluations presented in this study support the application of this model framework for global analysis of current and potential future budgets and deposition of N<sub>r</sub> and SIA.en_US
dc.identifier.citationGe, Heal, Stevenson, Wind, Vieno. Evaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements. Geoscientific Model Development. 2021;14:7021-7046en_US
dc.identifier.cristinIDFRIDAID 1967047
dc.identifier.doi10.5194/gmd-14-7021-2021
dc.identifier.issn1991-959X
dc.identifier.issn1991-9603
dc.identifier.urihttps://hdl.handle.net/10037/24054
dc.language.isoengen_US
dc.publisherCopernicus Publicationsen_US
dc.relation.journalGeoscientific Model Development
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2021 The Author(s)en_US
dc.titleEvaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurementsen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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