TY - JOUR
T1 - Evaluation of operational online-coupled regional air quality models over Europe and North America in the context of AQMEII phase 2. Part II
T2 - Particulate matter
AU - Im, Ulas
AU - Bianconi, Roberto
AU - Solazzo, Efisio
AU - Kioutsioukis, Ioannis
AU - Badia, Alba
AU - Balzarini, Alessandra
AU - Baró, Rocío
AU - Bellasio, Roberto
AU - Brunner, Dominik
AU - Chemel, Charles
AU - Curci, Gabriele
AU - Denier van der Gon, Hugo
AU - Flemming, Johannes
AU - Forkel, Renate
AU - Giordano, Lea
AU - Jiménez-Guerrero, Pedro
AU - Hirtl, Marcus
AU - Hodzic, Alma
AU - Honzak, Luka
AU - Jorba, Oriol
AU - Knote, Christoph
AU - Makar, Paul A.
AU - Manders-Groot, Astrid
AU - Neal, Lucy
AU - Pérez, Juan L.
AU - Pirovano, Guido
AU - Pouliot, George
AU - San Jose, Roberto
AU - Savage, Nicholas
AU - Schroder, Wolfram
AU - Sokhi, Ranjeet S.
AU - Syrakov, Dimiter
AU - Torian, Alfreida
AU - Tuccella, Paolo
AU - Wang, Kai
AU - Werhahn, Johannes
AU - Wolke, Ralf
AU - Zabkar, Rahela
AU - Zhang, Yang
AU - Zhang, Junhua
AU - Hogrefe, Christian
AU - Galmarini, Stefano
N1 - Funding Information:
We gratefully acknowledge the contribution of various groups to the second air Quality Model Evaluation international Initiative (AQMEII) activity: U.S. EPA, Environment Canada, Mexican Secretariat of the Environment and Natural Resources (Secretaría de Medio Ambiente y Recursos Naturales-SEMARNAT) and National Institute of Ecology (Instituto Nacional de Ecología-INE) (North American national emissions inventories); U.S. EPA (North American emissions processing); TNO (European emissions processing); ECMWF/MACC project & Météo-France/CNRM-GAME (Chemical boundary conditions). Ambient North American concentration measurements were extracted from Environment Canada's National Atmospheric Chemistry Database (NAtChem) PM database and provided by several U.S. and Canadian agencies (AQS, CAPMoN, CASTNet, IMPROVE, NAPS, SEARCH and STN networks); North American precipitation-chemistry measurements were extracted from NAtChem's precipitation-chemistry database and were provided by several U.S. and Canadian agencies (CAPMoN, NADP, NBPMN, NSPSN, and REPQ networks); the WMO World Ozone and Ultraviolet Data Centre (WOUDC) and its data-contributing agencies provided North American and European ozonesonde profiles; NASA's AErosol RObotic NETwork (AeroNet) and its data-contributing agencies provided North American and European AOD measurements; the MOZAIC Data Centre and its contributing airlines provided North American and European aircraft takeoff and landing vertical profiles; for European air quality data the following data centers were used: EMEP European Environment Agency/European Topic Center on Air and Climate Change/AirBase provided European air- and precipitation-chemistry data. The Finish Meteorological Institute is acknowledged for providing biomass burning emission data for Europe. Data from meteorological station monitoring networks were provided by NOAA and Environment Canada (for the US and Canadian meteorological network data) and the National Center for Atmospheric Research (NCAR) data support section. Joint Research Center Ispra/Institute for Environment and Sustainability provided its ENSEMBLE system for model output harmonization and analyses and evaluation. The co-ordination and support of the European contribution through COST Action ES1004 EuMetChem is gratefully acknowledged. The views expressed here are those of the authors and do not necessarily reflect the views and policies of the U.S. Environmental Protection Agency (EPA) or any other organization participating in the AQMEII project. This paper has been subjected to EPA review and approved for publication. C. Knote was supported by the DOE grant DE-SC0006711 . The UPM authors thankfully acknowledge the computer resources, technical expertise and assistance provided by the Centro de Supercomputación y Visualización de Madrid (CESVIMA) and the Spanish Supercomputing Network (BSC). G. Curci and P. Tuccella were supported by the Italian Space Agency (ASI) in the frame of PRIMES project (contract n. I/017/11/0 ). The Centre of Excellence for Space Sciences and Technologies SPACE-SI is an operation partly financed by the European Union , European Regional Development Fund and Republic of Slovenia, Ministry of Higher Education, Science, Sport and Culture . Y. Zhang acknowledges funding support from the NSF Earth System Program ( AGS-1049200 ) and high-performance computing support from Yellowstone by NCAR's Computational and Information Systems Laboratory , sponsored by the National Science Foundation and Stampede , provided as an Extreme Science and Engineering Discovery Environment (XSEDE) digital service by the Texas Advanced Computing Center (TACC). The technical assistance of Bert van Ulft (KNMI) and Arjo Segers (TNO) in producing the results of the RACMO2-LOTOS-EUROS system is gratefully acknowledged. L. Giordano was supported by the Swiss SERI COST project C11.0144 . UH-CAIR acknowledges support from the TRANSPHORM (FP7) project which provided the basis for their modelling approaches.
Publisher Copyright:
© 2014 Elsevier Ltd.
PY - 2015/8/1
Y1 - 2015/8/1
N2 - The second phase of the Air Quality Model Evaluation International Initiative (AQMEII) brought together seventeen modeling groups from Europe and North America, running eight operational online-coupled air quality models over Europe and North America using common emissions and boundary conditions. The simulated annual, seasonal, continental and sub-regional particulate matter (PM) surface concentrations for the year 2010 have been evaluated against a large observational database from different measurement networks operating in Europe and North America. The results show a systematic underestimation for all models in almost all seasons and sub-regions, with the largest underestimations for the Mediterranean region. The rural PM10 concentrations over Europe are underestimated by all models by up to 66% while the underestimations are much larger for the urban PM10 concentrations (up to 75%). On the other hand, there are overestimations in PM2.5 levels suggesting that the large underestimations in the PM10 levels can be attributed to the natural dust emissions. Over North America, there is a general underestimation in PM10 in all seasons and sub-regions by up to ~90% due mainly to the underpredictions in soil dust. SO42- levels over EU are underestimated by majority of the models while NO3- levels are largely overestimated, particularly in east and south Europe. NH4+ levels are also underestimated largely in south Europe. SO4 levels over North America are particularly overestimated over the western US that is characterized by large anthropogenic emissions while the eastern USA is characterized by underestimated SO4 levels by the majority of the models. Daytime AOD levels at 555nm is simulated within the 50% error range over both continents with differences attributed to differences in concentrations of the relevant species as well as in approaches in estimating the AOD. Results show that the simulated dry deposition can lead to substantial differences among the models. Overall, the results show that representation of dust and sea-salt emissions can largely impact the simulated PM concentrations and that there are still major challenges and uncertainties in simulating the PM levels.
AB - The second phase of the Air Quality Model Evaluation International Initiative (AQMEII) brought together seventeen modeling groups from Europe and North America, running eight operational online-coupled air quality models over Europe and North America using common emissions and boundary conditions. The simulated annual, seasonal, continental and sub-regional particulate matter (PM) surface concentrations for the year 2010 have been evaluated against a large observational database from different measurement networks operating in Europe and North America. The results show a systematic underestimation for all models in almost all seasons and sub-regions, with the largest underestimations for the Mediterranean region. The rural PM10 concentrations over Europe are underestimated by all models by up to 66% while the underestimations are much larger for the urban PM10 concentrations (up to 75%). On the other hand, there are overestimations in PM2.5 levels suggesting that the large underestimations in the PM10 levels can be attributed to the natural dust emissions. Over North America, there is a general underestimation in PM10 in all seasons and sub-regions by up to ~90% due mainly to the underpredictions in soil dust. SO42- levels over EU are underestimated by majority of the models while NO3- levels are largely overestimated, particularly in east and south Europe. NH4+ levels are also underestimated largely in south Europe. SO4 levels over North America are particularly overestimated over the western US that is characterized by large anthropogenic emissions while the eastern USA is characterized by underestimated SO4 levels by the majority of the models. Daytime AOD levels at 555nm is simulated within the 50% error range over both continents with differences attributed to differences in concentrations of the relevant species as well as in approaches in estimating the AOD. Results show that the simulated dry deposition can lead to substantial differences among the models. Overall, the results show that representation of dust and sea-salt emissions can largely impact the simulated PM concentrations and that there are still major challenges and uncertainties in simulating the PM levels.
KW - AQMEII
KW - Europe
KW - North America
KW - On-line coupled models
KW - Particulate matter
KW - Performance analysis
UR - http://www.scopus.com/inward/record.url?scp=84937717444&partnerID=8YFLogxK
U2 - 10.1016/j.atmosenv.2014.08.072
DO - 10.1016/j.atmosenv.2014.08.072
M3 - Article
AN - SCOPUS:84937717444
SN - 1352-2310
VL - 115
SP - 421
EP - 441
JO - Atmospheric Environment
JF - Atmospheric Environment
ER -