A single-point modeling approach for the intercomparison and evaluation of ozone dry deposition across chemical transport models (Activity 2 of AQMEII4).

A primary sink of air pollutants and their precursors is dry deposition. Dry deposition estimates differ across chemical transport models, yet an understanding of the model spread is incomplete. Here, we introduce Activity 2 of the Air Quality Model Evaluation International Initiative Phase 4 (AQMEII4). We examine 18 dry deposition schemes from regional and global chemical transport models as well as standalone models used for impact assessments or process understanding. We configure the schemes as single-point models at eight Northern Hemisphere locations with observed ozone fluxes. Single-point models are driven by a common set of site-specific meteorological and environmental conditions. Five of eight sites have at least 3 years and up to 12 years of ozone fluxes. The interquartile range across models in multiyear mean ozone deposition velocities ranges from a factor of 1.2 to 1.9 annually across sites and tends to be highest during winter compared with summer. No model is within 50 % of observed multiyear averages across all sites and seasons, but some models perform well for some sites and seasons. For the first time, we demonstrate how contributions from depositional pathways vary across models. Models can disagree with respect to relative contributions from the pathways, even when they predict similar deposition velocities, or agree with respect to the relative contributions but predict different deposition velocities. Both stomatal and nonstomatal uptake contribute to the large model spread across sites. Our findings are the beginning of results from AQMEII4 Activity 2, which brings scientists who model air quality and dry deposition together with scientists who measure ozone fluxes to evaluate and improve dry deposition schemes in the chemical transport models used for research, planning, and regulatory purposes.

Déclaration de conflit d'intérêts

Author contributions. OEC led the manuscript’s direction and writing, data processing and analysis, and coordination among authors. DS and CH contributed to the manuscript’s direction, data processing, and coordination among authors. JOB contributed CMAQ STAGE results and documentation. SB contributed DO3SE results and documentation. PC contributed GEM-MACH results and documentation. MC contributed data from Easter Bush and Auchencorth Moss. LE contributed DO3SE results and documentation and assisted with direction. JF contributed IFS results and documentation and assisted with direction. EF, QL, and ET contributed data from Ramat Hanadiv. SG assisted with direction. LG contributed MLC-CHEM results and documentation. OG, IG, and GM contributed data from Ispra. CDH assisted with direction and contributed GEOS-Chem results and documentation. LH and TW contributed data from Bugacpuszta. VH contributed model results and documentation from IFS. PAM contributed model results and documentation from GEM-MACH and assisted with direction. IM and TV contributed data from Hyytiälä. JWM contributed data from Harvard Forest. JLPC and RSJ contributed WRF-Chem results and documentation. JP and LR contributed M3Dry results and documentation. RS, ZW, and LZ contributed data from Borden Forest. SJS assisted with data processing and assisted with direction. SS and APKT contributed TEMIR results and documentation. All authors contributed to manuscript writing and useful discussions on data analysis and processing and results. Competing interests. At least one of the (co-)authors is a member of the editorial board of Atmospheric Chemistry and Physics. The peer-review process was guided by an independent editor, and the authors also have no other competing interests to declare.