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Influence of the choice of gas-phase mechanism on predictions of key gaseous pollutants during the AQMEII phase-2 intercomparison
Citation:
Knote, C., P. Tuccella, G. Curci, L. Emmons, J. Orlando, S. Madronich, R. Baro, P. Jimenez-Guerrero, D. Luecken, C. Hogrefe, R. Forkerl, J. Werhahn, M. Hirtl, J. Perez, R. San Jose, L. Giordano, D. Brunner, K. Yahya, AND Y. Zhang. Influence of the choice of gas-phase mechanism on predictions of key gaseous pollutants during the AQMEII phase-2 intercomparison. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, 115:553-568, (2015).
Impact/Purpose:
The National Exposure Research Laboratory’s Atmospheric Modeling Division (AMAD) conducts research in support of EPA’s mission to protect human health and the environment. AMAD’s research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the Nation’s air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements
Description:
The formulations of tropospheric gas-phase chemistry (“mechanisms”)used in the regional-scale chemistry-transport models participating in theAir Quality Modelling Evaluation International Initiative (AQMEII) Phase2 are intercompared by the means of box model studies. Simulations were conducted under idealized meteorological conditions, and the results are representative of mean boundary layer concentrations. Three sets of meteorological conditions - winter, spring/autumn and summer - were used to capture the annual variability, similar to the 3-D model simulations in AQMEII Phase 2. We also employed the same emissions input data used in the 3-D model intercomparison, and sample from these datasets employing different strategies to evaluate mechanism performance under a realistic range of pollution conditions.
URLs/Downloads:
KNOTE_ET_AL_MANUSCRIPT_FINAL.PDF (PDF, NA pp, 1638.745 KB, about PDF)Atmospheric Environment
